Database Querying and Interface Use involves the ability to efficiently retrieve, manipulate, and analyze data from complex databases using advanced querying techniques and user interfaces. This skill is critical for extracting actionable insights from Samsung's vast and diverse datasets, enabling data-driven decision-making that supports strategic objectives such as innovation in consumer electronics, semiconductors, and connected devices. Proficiency in this area ensures seamless interaction with database systems, allowing for the identification of trends, patterns, and opportunities that align with Samsung's mission to "Inspire the World, Create the Future." Mastery of database querying tools and interfaces also facilitates collaboration with cross-functional teams by providing accurate, timely, and well-structured data to inform recommendations and optimize business performance.
Learning Resources
Manipulating databases is a necessary skill. Explore Structured Query Language (SQL) and dive into the architecture. Discover efficient and easily manageable databases using features like SELECT, data types, UPDATE, and ORDER BY.
Master advanced queries. Queries in SQL allow you to manipulate databases like a pro. Discover advanced techniques including subqueries, correlated queries, difficult queries, and learn query tips for better efficiency.
To query data with SQL, you need to know which queries and keywords to use for which operations. In this course, you'll learn to query data using the classic SQL syntax construct, the SELECT-FROM-WHERE query, and how keywords, such as LIKE, can be used to filter data based on a condition and using wildcards. You'll learn how to carry out different aspects of inserting, updating, and deleting data …
Proficiency Levels
Novice
- Describes the primary types of databases used within Samsung’s business units, such as those supporting consumer electronics or semiconductor operations.
- Names common database querying languages and interfaces (e.g., SQL, data visualization tools) used for accessing Samsung’s datasets.
- Explains the basic structure of Samsung’s data repositories, including tables, fields, and relationships relevant to business analytics.
- Lists the key data sources and types of information typically analyzed to support decision making in areas like product development or supply chain management.
Intermediate
- Works with basic database queries to retrieve specific data sets for routine business reporting.
- Uses standard database interfaces to generate simple reports or dashboards for team meetings.
- Performs routine data cleansing activities to prepare datasets for further analysis or visualization.
- Follows established database access protocols to fulfill straightforward data requests.
- Assists in developing regular performance metrics for consumer electronics or semiconductor divisions.
Advanced ★ Required Level
- Evaluates the effectiveness of existing data models and recommends improvements to enhance reporting accuracy and efficiency.
- Monitors data extraction processes to identify potential sources of error or inefficiency and proposes corrective actions.
- Advises on the quality and completeness of data retrieved from various systems to ensure reliable insights for decision making.
- Designs complex queries to identify trends and patterns in large, multi source datasets relevant to strategic business initiatives.
- Trains others on integrating data from multiple databases to perform comparative analyses supporting product innovation or market expansion strategies.
- Oversees the interpretation and communication of data findings to cross functional teams, highlighting opportunities for operational improvement.
Expert
- Leads the creation of new data models that enable deeper analysis of consumer behavior or supply chain performance.
- Designs and implements advanced database queries and interfaces tailored to emerging business needs, such as AI driven analytics or sustainability tracking.
- Establishes best practices for database querying and interface use across teams.
- Develops automated data pipelines and dashboards that provide real time insights for executive decision makers.
- Demonstrates expertise in integrating disparate data sources to support the launch of new products or services.
- Creates documentation and training materials to standardize database querying and interface use.
Data Analysis and Modeling involves the ability to extract, interpret, and structure complex datasets to uncover actionable insights that drive strategic decision-making and operational efficiency. This skill encompasses advanced statistical techniques, predictive modeling, and data visualization to identify trends, patterns, and opportunities aligned with organizational goals. At Samsung, this expertise is critical for supporting innovation in areas such as consumer electronics, semiconductors, and connected devices, while contributing to sustainability and market leadership. Proficiency in this skill enables collaboration across cross-functional teams to develop data-driven recommendations that optimize business performance and align with Samsung's mission to "Inspire the World, Create the Future."
Learning Resources
Data science involves using scientific analysis, tools, and mathematics to extract useful insight from raw data, and then applying that knowledge for effective business strategy. Increasingly, companies are turning to data science. They can use scientific analysis, tools, and mathematics to extract useful insight from Big Data, to guide their decisions and drive business improvements. In this cour…
Data as a form of currency is an analogy that's been around since the early 2000s. However, data itself is worthless. The real value is in the insights you gain from it; this is where data analysis comes in. Data modeling is a crucial part of data analysis, helping turn raw data into accurate insights and meaningful reports. Use this course to learn how to design and optimize data models through P…
Data analytics is used across various industries to help companies make better-informed business decisions. Data analysts capture, process, and organize data in addition to establishing the best way to present that data. Through this course, learn about the uses and benefits of data analytics and the tools to leverage it. Examine the data analytics maturity model and compare the descriptive, diagn…
Proficiency Levels
Novice
- Describes the purpose and structure of standard data models and dashboards used within Samsung.
- Identifies and defines key data types and sources relevant to Samsung’s consumer electronics and semiconductor business.
- Explains how data driven insights contribute to Samsung’s mission and strategic objectives.
- Lists the steps involved in collecting, processing, and validating business data.
Intermediate
- Works with data collection, validation, and cleansing for routine business reporting.
- Uses basic data models and generates routine reports to visualize operational metrics.
- Follows established dashboards to monitor key performance indicators for specific product lines.
- Participates in addressing straightforward data requests from business units.
- Performs routine data analysis techniques to identify simple trends and patterns in sales or production data.
Advanced ★ Required Level
- Evaluates the effectiveness of existing data models and recommends improvements based on analytical findings.
- Monitors data quality issues and proposes solutions to enhance data integrity across multiple business functions.
- Advises cross functional teams on actionable insights derived from data visualizations.
- Designs processes to investigate anomalies or outliers in operational data and determine their root causes.
- Trains others on how to compare and contrast different analytical approaches to select the most appropriate method for a given business challenge.
- Oversees the analysis of complex datasets to uncover underlying trends and evaluate their impact on business performance.
Expert
- Leads the design and implementation of advanced data models tailored to support innovation in AI, IoT, or connected devices.
- Designs interactive dashboards that enable real time monitoring and decision making for strategic initiatives.
- Establishes cross functional projects to integrate new data sources and analytical tools into existing workflows.
- Develops predictive models to forecast market trends and inform product development strategies.
- Demonstrates customized data solutions that address unique business requirements in sustainability or supply chain optimization.
- Creates and drives the adoption of new data visualization techniques to enhance communication of complex insights.
Database Management is the ability to design, organize, and maintain complex databases to ensure the efficient storage, retrieval, and analysis of data. For a Data Analyst at Samsung, this skill involves managing large-scale datasets across diverse domains such as consumer electronics, semiconductors, and connected devices, ensuring data integrity and accessibility to support strategic decision-making. Proficiency in database management enables the analyst to structure data effectively, optimize query performance, and integrate data from multiple sources, aligning with Samsung's mission to drive innovation and operational excellence. This expertise is critical for identifying trends and opportunities that contribute to achieving Samsung's strategic objectives, including advancements in AI, sustainability, and market leadership.
Learning Resources
Databases are the backbone of modern life, powering everything from online shopping to social media to memberships and countless other activities. They enable us to store, manage, and retrieve vast amounts of information quickly and efficiently. Understanding databases is the very first step in mastering data analytics. In this course, you will explore databases, beginning with the basic concepts …
Most businesses are unable to function without a database, even if it's just a filing cabinet. With more and more data coming from multiple sources comes an increased demand for secure and well-performing databases with adequate storage. Take this course to get a firm understanding of what exactly data means and why a database management system (DBMS) is so important for data management. Examine t…
A Database Management System, also known as a DBMS, is used to control, store, organize, and retrieve that data. Discover databases, DBMS, and RDBMS, and explore different database models.
Proficiency Levels
Novice
- Describes the primary types of databases used at Samsung, such as relational and NoSQL databases.
- Identifies key database terminology, including tables, schemas, queries, and indexes, relevant to Samsung’s data landscape.
- Explains the importance of data integrity and security in managing sensitive business information.
- Lists common data sources and systems integrated into Samsung’s analytics environment.
Intermediate
- Works with database management tools to organize and store data for specific business units or projects.
- Participates in basic data validation and cleansing activities to support data quality in ongoing projects.
- Assists in generating standard reports and dashboards using data pulled from multiple internal sources.
- Uses routine data extraction queries to retrieve information from Samsung’s databases for business reporting.
- Follows established protocols to back up and restore database information as required.
Advanced ★ Required Level
- Evaluates the performance of existing database queries and recommends optimizations for efficiency.
- Monitors and resolves data inconsistencies or integrity issues within large scale datasets.
- Advises on the suitability of different database structures for new analytics initiatives in AI or IoT.
- Designs data flows between systems to identify bottlenecks or risks impacting business operations.
- Trains others on reviewing and validating data models to ensure alignment with business requirements and reporting needs.
- Oversees cross functional teams to troubleshoot complex data integration challenges.
Expert
- Leads the design and implementation of new database schemas to support emerging business needs in connected devices or semiconductor analytics.
- Develops automated data pipelines that integrate information from diverse sources for advanced analytics.
- Creates scalable data models that enable real time reporting and decision making.
- Establishes protocols for data governance and quality assurance across multiple business domains.
- Demonstrates new methods for optimizing query performance in high volume transactional environments.
- Designs solutions for secure data sharing between teams while maintaining compliance with privacy standards.
Data Visualization and Analysis involves the ability to transform complex datasets into clear, actionable insights through the use of advanced visualization tools and techniques. This skill enables the identification of trends, patterns, and opportunities that align with Samsung's strategic objectives, such as driving innovation in consumer electronics, semiconductors, and connected devices. Proficiency in this area supports effective communication of data-driven findings to cross-functional teams, fostering collaboration and informed decision-making. By leveraging this expertise, the Data Analyst contributes to enhancing operational efficiency, optimizing business performance, and advancing Samsung's mission to "Inspire the World, Create the Future."
Learning Resources
Data visualization prepares data for presentation to make it easier for non-data analysts to understand what the data is saying. Often, non-data analysts can't see relationships in data without visual aids, but effective data presentation allows them to change parameters and understand and view the data in a similar manner to a data scientist. In this course, explore the purpose and key considerat…
Data is meaningful only when information is extracted from it. That information can tell a story, and the best data analysts are magnificent storytellers. But no matter how accomplished a data analyst, a story can't be told compellingly without visualizing what the data says and a key part of a data analyst's role is in reporting on what the data is saying. In this course, you will explore data vi…
The business world is full of data. Using this data strategically presents a company with serious competitive advantages. The tricky part is making sense of the data and then communicating what it means. Data visualization (or data viz, for short) provides actionable insights out of what can be complex sets of data. In this course, you'll learn the considerations for creating data visualizations a…
Proficiency Levels
Novice
- Describes the importance of data quality and integrity in supporting business decisions at Samsung.
- Explains how data driven insights contribute to Samsung’s mission and strategic objectives.
- Identifies key data sources relevant to Samsung’s consumer electronics and semiconductor business units.
- Lists the steps involved in collecting and processing raw business data.
Intermediate
- Works with standard data visualization tools to represent sales or operational trends.
- Uses data analysis methods to identify routine patterns in consumer behavior or supply chain performance.
- Participates in developing basic dashboards to monitor key performance indicators for a specific product line.
- Assists in gathering and organizing data for regular reporting cycles.
- Performs data validation techniques to ensure accuracy in routine business reports.
Advanced ★ Required Level
- Evaluates the effectiveness of existing data models and recommends improvements for greater accuracy.
- Monitors the impact of data driven recommendations on business performance and strategic objectives.
- Advises on data anomalies or inconsistencies and determines their potential business implications.
- Designs comprehensive insights for cross functional projects by synthesizing data from multiple sources.
- Trains others to interpret data visualizations to diagnose operational inefficiencies and propose actionable solutions.
- Oversees the analysis of complex datasets to uncover emerging trends in premium smartphone or semiconductor markets.
Expert
- Leads the creation of predictive models to forecast market demand for emerging product categories.
- Designs advanced, interactive dashboards that enable real time monitoring of sustainability metrics.
- Develops innovative data visualization frameworks tailored to new AI or IoT business initiatives.
- Creates customized data analysis workflows that address unique challenges in supply chain optimization.
- Establishes best practices for integrating disparate data sources to build unified reporting systems for executive decision making.
- Demonstrates thought leadership by championing the adoption of new visualization tools or techniques to enhance organizational data literacy.
Mathematics is a critical skill for the Data Analyst role at Samsung, enabling the precise analysis and interpretation of complex datasets to uncover trends, patterns, and actionable insights. This skill encompasses a strong foundation in statistical methods, probability, and quantitative reasoning, which are essential for developing data-driven recommendations that align with Samsung's strategic objectives. Proficiency in mathematics supports the application of advanced analytical techniques, such as predictive modeling and optimization, to drive innovation and enhance operational efficiency across diverse areas like consumer electronics, semiconductors, and connected devices. By leveraging mathematical expertise, the Data Analyst contributes to informed decision-making and the achievement of Samsung's mission to "Inspire the World, Create the Future."
Learning Resources
Data science involves using scientific analysis, tools, and mathematics to extract useful insight from raw data, and then applying that knowledge for effective business strategy. Increasingly, companies are turning to data science. They can use scientific analysis, tools, and mathematics to extract useful insight from Big Data, to guide their decisions and drive business improvements. In this cour…
A fundamental understanding of statistical analysis methods increases your ability to effectively communicate with data analyst professionals so you can better employ analytics associated with your work. In this course, you'll learn fundamental concepts in distribution, deviation, correlation, regression, and clustering statistical analysis methods. This course was developed with subject matter pr…
Data is rarely received in perfect form and often requires some sort of manipulation to make it sing. That is why the world needs data analysts. They can squeeze every bit of usefulness from datasets, and they also know how to prep datasets to extract meaning from them. In this course, you will explore key concepts of data manipulation, beginning with data manipulation tools. Then you will learn o…
Proficiency Levels
Novice
- Describes the role of probability in interpreting trends within operational and market data.
- Identifies and defines key mathematical concepts such as mean, median, mode, and standard deviation relevant to data analysis at Samsung.
- Explains the importance of mathematical accuracy in supporting Samsung’s strategic decision making.
- Lists the steps involved in validating and cleansing raw data for quality assurance.
Intermediate
- Uses basic statistical methods to analyze and interpret data for routine business reports.
- Performs data validation checks to ensure accuracy and integrity in operational datasets.
- Develops simple data visualizations to communicate findings to cross functional teams.
- Applies probability distributions to forecast demand for specific products in predictable market scenarios.
- Utilizes mathematical formulas to automate routine calculations in dashboards and reports.
Advanced ★ Required Level
- Evaluates the effectiveness of predictive models in forecasting sales trends for new product launches.
- Monitors the impact of data anomalies on business insights and recommends corrective actions using quantitative reasoning.
- Advises on the interpretation of multivariate analysis results to support strategic decisions in AI chip development or connected device innovation.
- Designs mathematical approaches to optimize data cleansing processes for improved data quality.
- Trains others on the use of advanced statistical techniques to uncover hidden patterns in consumer behavior or supply chain performance.
- Oversees the accuracy, relevance, and alignment of data models and dashboards with Samsung’s strategic objectives.
Expert
- Leads the development of advanced mathematical models to predict market shifts and inform product development strategies.
- Designs innovative algorithms for real time data analysis in support of sustainability and operational efficiency initiatives.
- Establishes dynamic dashboards that integrate complex statistical outputs for executive decision making.
- Develops optimization models to enhance resource allocation in semiconductor manufacturing or supply chain operations.
- Demonstrates new methods for integrating mathematical analysis into cross functional collaboration processes.
- Creates custom data validation frameworks that set new standards for data integrity across business units.
Critical Thinking is the ability to objectively analyze and evaluate complex information to form well-reasoned judgments and solutions. For a Data Analyst at Samsung, this skill involves dissecting intricate datasets to uncover meaningful trends, patterns, and opportunities that align with the company’s mission to "Inspire the World, Create the Future." It requires a systematic approach to problem-solving, enabling the identification of innovative strategies that enhance operational efficiency and support strategic decision-making. Critical Thinking also encompasses the capacity to challenge assumptions, synthesize diverse perspectives, and collaborate effectively with cross-functional teams to drive actionable insights in areas such as consumer electronics, semiconductors, and connected devices. This skill is essential for optimizing business performance and contributing to Samsung’s goals in sustainability, AI development, and market leadership.
Learning Resources
It often seems like the whole world is on information overload. Each day, we encounter massive amounts of new false, or dubious information, alongside a steady stream of data that may, or may not, be relevant to our needs. As a leader, your critical thinking skills are essential for deciding what is important and making the best decisions for your organization. This course will help you improve yo…
The focus in business today is collaboration - working together to solve complex problems. But just collaborating won't get you to the finish line. You must be able to think critically, which means decomposing problems, avoiding biases, looking for flaws in your thinking, and developing the best solution. In this Leadercamp, PMP Merri Lemmex explores critical thinking, how you can avoid habits tha…
Computational thinking is a structured way to understand and solve the kind of complex problems facing most organizations today. First developed in conjunction with developing computer systems, it can be applied to many situations, both computerized and not. And it can help determine the right types of computer and human actions to apply in order to solve a problem. In this course, you'll learn th…
Proficiency Levels
Novice
- Describes the basic steps involved in collecting, processing, and validating business data.
- Explains the role of data analysis in supporting cross functional collaboration within Samsung.
- Identifies and defines key data concepts relevant to Samsung’s consumer electronics and semiconductor businesses.
- Lists common data sources and types used in operational and strategic decision making at Samsung.
Intermediate
- Works with basic data analysis tools and techniques to support routine business needs.
- Uses standard data validation and cleansing procedures to ensure accuracy in regular datasets.
- Assists in developing standard data visualizations and dashboards to communicate findings to team members.
- Follows Samsung’s data governance guidelines when handling and processing sensitive business information.
- Participates in cross functional teams by providing routine data extracts and summaries for ongoing projects.
Advanced ★ Required Level
- Evaluates the effectiveness of current data models and recommends improvements to enhance business insights.
- Monitors the quality and reliability of data sources used in strategic projects, identifying potential risks.
- Advises on root causes of data inconsistencies and proposes solutions to improve data integrity.
- Designs complex datasets to identify emerging trends and patterns impacting Samsung’s product lines.
- Trains others on interpreting data findings to provide actionable recommendations for optimizing operational efficiency.
- Oversees the impact of data driven decisions on business outcomes.
Expert
- Leads the design of innovative data models and analytical frameworks to address new business challenges in AI or IoT.
- Develops advanced dashboards and reporting systems that enable real time decision making for leadership.
- Leads cross functional workshops to co create data driven strategies for sustainability and market growth.
- Integrates diverse data sources to create holistic views of business performance across product lines.
- Develops predictive analytics solutions to anticipate market shifts and inform product development.
- Creates protocols for advanced data validation and cleansing tailored to Samsung’s evolving business needs.
Reading Comprehension is the ability to thoroughly understand, interpret, and analyze written information to extract meaningful insights and actionable conclusions. For a Data Analyst at Samsung, this skill is critical for reviewing complex datasets, technical documentation, and industry reports to identify trends and opportunities that align with the company’s strategic objectives. It involves discerning key details, synthesizing information from diverse sources, and contextualizing findings within Samsung’s focus areas, such as sustainability, AI development, and market leadership in premium technology solutions. Strong reading comprehension ensures effective collaboration with cross-functional teams and supports the development of data-driven recommendations that drive innovation and operational efficiency.
Learning Resources
Most current question answering datasets will frame the task as reading comprehension, where the question is about a paragraph or document and the answer often is a span in the document. Some specific tasks of reading comprehension include multi-modal machine reading comprehension and textual machine reading comprehension, among others. This course focuses on the architecture of the Q&A pipeline. …
Data is meaningful only when information is extracted from it. That information can tell a story, and the best data analysts are magnificent storytellers. But no matter how accomplished a data analyst, a story can't be told compellingly without visualizing what the data says and a key part of a data analyst's role is in reporting on what the data is saying. In this course, you will explore data vi…
As industries, enterprises, and jobs become more data-intensive, data literacy is critical to effectively "talk data" with business colleagues and data and analytics professionals who support you in your work. This course covers fundamental concepts in data management, data quality, data privacy and protection, and data governance. This course was developed with subject matter provided by the Inte…
Proficiency Levels
Novice
- Describes the purpose of a specific data model or dashboard used in routine reporting.
- Identifies the main points from internal data quality guidelines and standard operating procedures.
- Explains the objectives of a data analysis project as outlined in project briefs.
- Lists common data sources and reporting formats used within Samsung’s business units.
Intermediate
- Uses written instructions to complete routine data analysis tasks.
- Follows established protocols to ensure data integrity during collection and processing.
- Works with technical documentation to validate data for analysis.
- Participates in the creation of standard reports and dashboards by interpreting cross functional instructions.
- Assists in identifying and correcting data inconsistencies using data quality manuals.
Advanced ★ Required Level
- Monitors the accuracy and completeness of technical documentation to ensure data integrity.
- Advises on the relevance and reliability of information from multiple written sources.
- Designs data models and reporting approaches based on stakeholder feedback.
- Trains others to synthesize information from diverse written materials to support recommendations.
- Oversees the review of complex datasets and documentation to identify trends and anomalies.
- Evaluates industry reports to assess their impact on strategic objectives.
Expert
- Leads the development of training materials that improve team reading comprehension of technical and business documents.
- Designs comprehensive data review processes that incorporate best practices from technical and industry literature.
- Establishes protocols for evaluating and incorporating new written data sources into existing analytical workflows.
- Develops guidelines for interpreting and synthesizing written information to enhance cross functional collaboration.
- Demonstrates the ability to author clear, actionable summaries of complex analytical findings for executive decision makers.
- Creates frameworks for integrating insights from technical documentation and market reports into data driven strategies.
Complex Problem Solving involves the ability to analyze multifaceted challenges, identify underlying patterns, and develop innovative solutions that align with organizational goals. For a Data Analyst at Samsung, this skill is critical in navigating and interpreting large, complex datasets to uncover actionable insights that drive strategic decision-making and operational efficiency. It requires a combination of logical reasoning, creativity, and advanced analytical techniques to address issues in dynamic areas such as consumer electronics, semiconductors, and connected devices. This skill also entails collaborating with cross-functional teams to devise recommendations that support Samsung's mission of innovation, sustainability, and market leadership in premium technology solutions.
Learning Resources
The effective use of analytics tools and techniques is a key requirement when analyzing the business problems your organization is currently dealing with. However, it's vital that you also possess a strong set of personal skills to help you process and understand the large amounts of data you'll likely come across during your analysis. In this course, you'll learn about some of the personal compet…
Data science involves using scientific analysis, tools, and mathematics to extract useful insight from raw data, and then applying that knowledge for effective business strategy. Increasingly, companies are turning to data science. They can use scientific analysis, tools, and mathematics to extract useful insight from Big Data, to guide their decisions and drive business improvements. In this cour…
Data is rarely received in perfect form and often requires some sort of manipulation to make it sing. That is why the world needs data analysts. They can squeeze every bit of usefulness from datasets, and they also know how to prep datasets to extract meaning from them. In this course, you will explore key concepts of data manipulation, beginning with data manipulation tools. Then you will learn o…
Proficiency Levels
Novice
- Describes the basic concepts and principles of data analysis.
- Identifies key data sources and common data quality issues.
- Explains the importance of data driven decision making.
- Lists the steps involved in collecting, processing, and analyzing business data.
Intermediate
- Works with data analysis tools to support routine business reporting.
- Uses standard data cleansing procedures to ensure accuracy and integrity of datasets.
- Performs routine data validation checks to maintain data quality in ongoing projects.
- Assists in generating basic reports and dashboards to visualize trends in sales or production data.
- Follows established data models to support routine analysis for cross functional teams.
Advanced ★ Required Level
- Evaluates the effectiveness of current data models and recommends improvements to enhance insight generation.
- Monitors complex datasets to identify emerging trends and patterns impacting product performance or market share.
- Advises on the root causes of data inconsistencies and proposes solutions to address them.
- Designs advanced analytical techniques to assess the impact of supply chain disruptions on business performance.
- Trains others to interpret data findings to support strategic decisions in areas such as AI development or sustainability initiatives.
- Oversees cross functional teams to evaluate data needs and ensure analytical solutions align with business objectives.
Expert
- Leads the development of new data validation frameworks to improve data quality organization wide.
- Designs and implements innovative data models that address new business challenges in connected devices or semiconductor manufacturing.
- Establishes advanced dashboards and visualization tools to communicate complex insights to executive leadership.
- Develops predictive analytics solutions to forecast market trends and inform product development strategies.
- Demonstrates the ability to lead cross functional projects to solve multifaceted business problems using creative analytical approaches.
- Creates and drives the adoption of advanced analytical techniques to optimize operational efficiency and support sustainability goals.
Programming, as a critical skill for the Data Analyst role at Samsung, involves the ability to write, debug, and optimize code to manipulate, analyze, and visualize complex datasets effectively. This skill enables the development of custom scripts and algorithms to uncover trends, patterns, and actionable insights that align with Samsung's strategic objectives, such as advancing AI, sustainability, and market leadership in premium technology solutions. Proficiency in programming languages like Python, R, or SQL is essential for automating data workflows, integrating diverse data sources, and building scalable analytical models. Additionally, programming supports collaboration with cross-functional teams by enabling the creation of tools and solutions that drive innovation across Samsung's diverse product and technology portfolio.
Learning Resources
There are many software and programming tools for data scientists. Before applying these tools effectively, you must understand underlying concepts. Explore data analysis concepts for effectively employing software and programming tools.
Data that lives in a database is only part of the equation when considering data analytics. Data needs to be accessed and processed in order to be useful. The importance of data in the modern world can easily be observed by considering the sheer number of data analytics tools. Without these tools, data loses some of its usefulness. In this course, you will explore popular data analytics tools, beg…
An essential skill for statistical computing and graphics. The programming language R the tool of choice for data science professionals in every industry and field-both to take advantage of R's great graphic and charting capabilities and to create reproducible high-quality analyses. In this 8-video Skillsoft Aspire course, you will discover how to use R to import and export tabular data in CSV (co…
Proficiency Levels
Novice
- Describes the steps involved in collecting, processing, and preparing data for analysis within Samsung’s business context.
- Identifies and describes the primary programming languages used for data analysis at Samsung, such as Python, R, and SQL.
- Explains the purpose of data validation and cleansing in ensuring data quality and integrity.
- Lists standard libraries and packages commonly used for data analysis and visualization (e.g., pandas, numpy, matplotlib).
Intermediate
- Works with basic data manipulation and visualization tools to support business operations.
- Uses programming to automate routine data validation and cleansing tasks.
- Assists in developing simple scripts to extract, clean, and preprocess data from internal databases.
- Participates in building and maintaining straightforward dashboards for cross functional teams.
- Performs basic data visualizations to communicate trends in consumer electronics sales.
Advanced ★ Required Level
- Designs and executes scripts to identify complex patterns and correlations in large, multi source datasets.
- Evaluates the effectiveness of different data models and algorithms in predicting market trends for premium devices.
- Oversees the debugging and optimization of existing code to improve the efficiency and accuracy of data processing workflows.
- Advises on programming based solutions to enhance data integrity across business units.
- Monitors the impact of data driven recommendations on operational efficiency and strategic objectives.
- Trains cross functional teams to evaluate data requirements and develop tailored analytical solutions.
Expert
- Leads the development of advanced analytical models and custom algorithms to support AI and IoT initiatives.
- Designs and implements automated data pipelines that integrate diverse data sources across Samsung’s product portfolio.
- Creates interactive dashboards and visualization tools that enable real time monitoring of sustainability metrics.
- Establishes programming solutions that address emerging business challenges in semiconductor manufacturing.
- Develops new methods for data collection and analysis that drive product and process improvements.
- Demonstrates expertise in architecting robust data validation frameworks to ensure high data quality for strategic decision making.
Judgment and Decision Making is the ability to evaluate complex datasets, scenarios, and potential outcomes to make informed, data-driven decisions that align with organizational goals. For a Data Analyst at Samsung, this skill involves synthesizing insights from diverse data sources to identify trends, assess risks, and prioritize opportunities that support strategic initiatives in areas like consumer electronics, semiconductors, and connected devices. It requires balancing analytical rigor with practical considerations to recommend actionable solutions that drive innovation, operational efficiency, and market leadership. This skill is critical for navigating Samsung's dynamic, competitive environment and contributing to its mission of inspiring the world and creating the future.
Learning Resources
Organizations around the world are now realizing the many advantages of using data to overhaul their business strategies and gain a competitive edge. However, data-driven decision making doesn't mean you have to ignore your intuition or past experience. In fact, when used in combination with business acumen, building a data-driven decision-making culture can be a powerful tool for change. In this …
Final Exam: Decision Analyst will test your knowledge and application of the topics presented throughout the Decision Analyst track of the Skillsoft Aspire Business Analyst to Data Analyst Journey.
Business analysts rely on a wide array of analytical techniques to uncover insights, evaluate data, define solutions, and support strategic decisions. Choosing the right technique ensures that analysis is thorough, data-driven, and aligned with business needs. In this course, explore essential analytical techniques used in business analysis, including benchmarking, document and process analysis, o…
Proficiency Levels
Novice
- Describes the role of data analysis in supporting sustainability and innovation initiatives at Samsung.
- Identifies key data sources relevant to consumer electronics and semiconductor business areas.
- Explains the process for collecting and processing business data within Samsung’s operational framework.
- Lists the main types of data models and dashboards used to visualize business performance.
Intermediate
- Works with basic data analysis tools to support business decision making.
- Uses established data validation procedures to ensure accuracy in routine business reports.
- Follows Samsung’s data governance guidelines when handling and sharing business data.
- Participates in data cleansing activities to address common data integrity issues.
- Assists in developing basic dashboards to visualize trends in consumer electronics or semiconductor sales.
Advanced ★ Required Level
- Evaluates the effectiveness of data models in supporting strategic decision making for new product launches.
- Monitors emerging trends and patterns in complex datasets impacting product performance.
- Advises on risks and opportunities in market data to inform premium smartphone strategies.
- Designs processes to synthesize insights from multiple data sources for sustainability initiatives.
- Trains others on data quality processes and recommends improvements for data integrity.
- Oversees the impact of data driven recommendations on business outcomes with cross functional teams.
Expert
- Leads the development of advanced data models and dashboards for AI and connected device initiatives.
- Designs innovative analytical frameworks for semiconductor manufacturing expansion.
- Establishes data driven strategies to optimize operational efficiency across business units.
- Develops methods to integrate new data sources and analytical techniques for enhanced insights.
- Demonstrates expertise in creating reporting systems aligned with sustainability and market leadership goals.
- Creates solutions for complex data challenges in cross functional projects.
Object-Oriented Programming (OOP) is a critical skill for the Data Analyst role at Samsung, enabling the development of modular, reusable, and efficient code to analyze and process complex datasets. This skill involves applying OOP principles such as encapsulation, inheritance, and polymorphism to create scalable data models and algorithms that support Samsung's strategic objectives, including innovation in AI, IoT, and connected devices. Proficiency in OOP allows the Data Analyst to collaborate effectively with cross-functional teams, integrating data-driven insights into actionable recommendations that enhance operational efficiency and drive market leadership. Mastery of this skill ensures the ability to design robust analytical solutions that align with Samsung's mission to "Inspire the World, Create the Future."
Learning Resources
If you're learning computer programming, you need to know what object-oriented programming (OOP) is. One of the most prolific and frequently used programming paradigms, OOP has many benefits, such as code reusability, maintenance, scalability, and collaboration. The pragmatic structure of OOP means you can build large and complex programs with ease and efficiency. Use this course to examine what c…
Object-oriented programming(OOP) is a programming method based on the concepts of 'objects' that contain properties and methods. Objects can inherit their structure from other classes and interfaces, which allows for code reuse. In this course, you'll learn about the features of object-oriented programming. First, you'll learn about the basics of object-oriented programming and how it relates to J…
In this course we adopt the object-oriented analysis and design (OOAD) methodology for developing computer programs. This methodology guides the developer into the proper structure for developing programs. We will begin by looking at this methodology to see how it helps the programmer develop better computer programs and consider how this approach compares to the traditional procedural style of so…
Proficiency Levels
Novice
- Describes the benefits of using OOP for maintaining data quality and integrity in analytical workflows.
- Identifies key object oriented programming concepts such as classes, objects, inheritance, and encapsulation as they relate to data analysis at Samsung.
- Explains how OOP principles can improve code modularity and reusability in the context of building data models for consumer electronics or semiconductor datasets.
- Lists examples of how OOP is applied in developing dashboards or reports for cross functional teams at Samsung.
Intermediate
- Uses encapsulation to protect and manage access to sensitive data attributes in analytical scripts.
- Works with inheritance to extend existing data models for new product lines or business requirements.
- Participates in the development of simple classes and objects to organize and process structured data from business units.
- Performs routine data validation and cleansing tasks using OOP techniques to improve data integrity.
- Assists in the construction of reusable code modules for generating standard reports and dashboards for operational teams.
Advanced ★ Required Level
- Evaluates the scalability and maintainability of existing OOP code used in analytical projects supporting AI or IoT initiatives.
- Monitors the effectiveness of OOP based data models in identifying trends and patterns across diverse datasets, such as sales or supply chain data.
- Advises on the impact of OOP driven automation on data quality and operational efficiency in cross functional projects.
- Designs solutions to resolve issues in complex OOP codebases that impact the accuracy or timeliness of business insights.
- Trains others on how to compare different OOP design patterns to determine the most suitable approach for a given data analysis challenge.
- Oversees code reviews to ensure adherence to OOP best practices and Samsung’s coding standards.
Expert
- Leads the creation of modular data processing pipelines using OOP principles to enable rapid adaptation to evolving business requirements.
- Designs and implements advanced OOP frameworks to support the development of scalable, reusable analytical solutions for new product launches or market analysis.
- Develops custom OOP based libraries or tools that streamline data collection, processing, and visualization for strategic initiatives such as sustainability reporting.
- Creates and deploys new OOP based algorithms that optimize operational efficiency and support Samsung’s leadership in technology innovation.
- Establishes robust OOP solutions that integrate data from multiple sources, supporting innovation in AI, IoT, or connected device analytics.
- Demonstrates leadership in cross functional projects that leverage OOP to enhance the quality and accessibility of business intelligence dashboards.
Proficiency in Integrated Development Environments (IDEs) is essential for a Data Analyst at Samsung to efficiently manage, analyze, and visualize complex datasets. This skill involves leveraging IDEs to streamline workflows, write and debug code, and integrate various data analysis tools and libraries. A strong command of IDEs enables seamless collaboration with cross-functional teams, ensuring the development of actionable insights that align with Samsung's strategic objectives, such as advancing AI, sustainability, and market leadership. Mastery of this skill supports the creation of innovative solutions in consumer electronics, semiconductors, and connected devices, driving operational efficiency and informed decision-making.
Learning Resources
There are many software and programming tools for data scientists. Before applying these tools effectively, you must understand underlying concepts. Explore data analysis concepts for effectively employing software and programming tools.
The Visual Studio IDE promotes and supports the principle of quality within the development cycle. Explore coding disciplines and testing practices to provide quality validation and implement project management.
Proficiency Levels
Novice
- Describes the basic features and functions of IDEs used in data analysis at Samsung.
- Explains the role of IDEs in visualizing data findings through built in tools and extensions.
- Lists the steps for connecting an IDE to internal data sources relevant to consumer electronics and semiconductor datasets.
- Names the primary features and functions of commonly used IDEs for data analysis at Samsung.
Intermediate
- Uses an IDE to import, clean, and preprocess raw business data for routine reporting tasks.
- Develops and executes basic data analysis scripts within an IDE to generate summary statistics for operational efficiency metrics.
- Creates and modifies simple data visualizations in the IDE to communicate trends in consumer electronics sales.
- Leverages IDE features to debug and troubleshoot errors in data processing scripts for regular business reports.
- Utilizes version control integration within the IDE to manage and track changes to data models and dashboards.
Advanced ★ Required Level
- Evaluates the effectiveness of different IDE plugins and extensions for advanced data modeling and visualization.
- Monitors the quality and reliability of data outputs generated through IDE based workflows for sustainability reporting.
- Advises on the most actionable insights for strategic decision making by comparing multiple data analysis approaches within the IDE.
- Designs solutions to resolve data integration issues within the IDE when collaborating with cross functional teams on AI development projects.
- Trains others on how to analyze complex datasets in the IDE to identify patterns and anomalies impacting semiconductor production efficiency.
- Oversees the optimization of existing data processing scripts in the IDE to improve performance and accuracy in business intelligence tasks.
Expert
- Leads the development of collaborative IDE environments that enable seamless teamwork across global business units.
- Designs and implements custom IDE workflows that streamline the end to end process of collecting, processing, and visualizing data for new product launches.
- Develops advanced, reusable data analysis templates and dashboards within the IDE to support ongoing market leadership initiatives.
- Creates and documents best practice guidelines for using IDEs in advanced data analysis projects aligned with Samsung’s strategic objectives.
- Establishes processes for integrating multiple data sources and analytical tools within the IDE to create comprehensive solutions for connected device analytics.
- Demonstrates innovative methods for automating data cleansing and validation processes in the IDE to support sustainability and compliance goals.
Create Effective Presentations involves the ability to design and deliver clear, compelling, and visually engaging presentations that effectively communicate complex data insights to diverse audiences. This skill requires proficiency in translating analytical findings into actionable narratives that align with Samsung's strategic objectives, such as innovation in consumer electronics, sustainability, and AI development. It also entails tailoring content to resonate with cross-functional teams and stakeholders, ensuring alignment with organizational goals and fostering informed decision-making. Mastery of this skill supports the Data Analyst's role in driving impactful recommendations and enhancing operational efficiency across Samsung's global enterprise.
Learning Resources
Crafting and delivering exceptional virtual presentations isn't merely a skill; it's a strategic imperative in this digital age. As the lines between physical and virtual communication blur, whether you're a business leader, educator, salesperson, or creative professional, your prowess in building and delivering compelling virtual presentations can significantly amplify your influence, foster enga…
In today's data-driven world, mastering data visualization is essential for driving digital transformation and making well-informed decisions. In this course, you'll gain the skills needed to create clear, accurate, and impactful visual representations of data. In this course, you'll learn about the importance and types of data visualization and how it supports informed decision-making. You'll als…
Delivering a powerful message requires the message to be succinct, clear, and compelling. Even if a presentation looks great, has all the facts right, and is based on a lot of solid work, it isn't enough. In this course, you will learn about best practices to ensure your message is effectively positioned for your target audience to enable action. This course was developed with subject matter provi…
Proficiency Levels
Novice
- Describes the basic steps involved in creating a data presentation for a specific audience.
- Lists the standard tools and software used at Samsung for creating and delivering data presentations.
- Explains the importance of tailoring presentation content to different internal audiences, such as product teams or executives.
- Identifies common data visualization formats (e.g., bar charts, line graphs, dashboards) and their purposes in communicating insights.
Intermediate
- Uses Samsung approved templates to visualize and communicate data trends related to consumer electronics sales.
- Develops a simple presentation that summarizes key findings from a routine data analysis project for a cross functional team.
- Presents data driven recommendations to a small internal group, ensuring clarity and alignment with business objectives.
- Incorporates feedback from team members to refine and improve the clarity of a data presentation.
- Applies basic storytelling techniques to explain the significance of data insights in a routine business review meeting.
Advanced ★ Required Level
- Evaluates the effectiveness of different presentation formats in communicating complex semiconductor data to technical and non technical stakeholders.
- Monitors audience feedback to identify areas for improvement in the delivery and design of data presentations.
- Advises on adapting presentation content and visuals to address the specific needs and concerns of diverse business units, such as marketing or R&D.
- Designs presentation narratives that align with Samsung’s strategic initiatives, such as sustainability or AI development.
- Trains others on integrating multiple data sources to create comprehensive presentations that support cross functional decision making.
- Oversees the review and validation of the accuracy and relevance of data visualizations before presenting to senior leadership.
Expert
- Leads the development of interactive dashboards and visual storytelling tools for use by global teams across Samsung.
- Designs and delivers innovative presentations that synthesize complex data insights to support new product launches or strategic initiatives.
- Establishes best practices for visualizing and presenting data related to sustainability and environmental impact.
- Develops customized presentation frameworks that enable rapid communication of data driven recommendations for emerging business opportunities.
- Demonstrates expertise in piloting new presentation technologies or formats to enhance engagement and understanding among executive stakeholders.
- Creates presentations in collaboration with cross functional leaders to drive alignment on AI and IoT strategies.
Active Learning is the ability to continuously acquire, process, and apply new knowledge and skills to adapt to evolving challenges and opportunities. For a Data Analyst at Samsung, this skill involves staying updated on the latest analytical techniques, industry trends, and technological advancements to uncover actionable insights from complex datasets. It requires a proactive approach to learning, enabling the analyst to identify innovative solutions that align with Samsung's mission to "Inspire the World, Create the Future" and its strategic objectives in areas such as AI, sustainability, and market leadership. By fostering a mindset of curiosity and adaptability, Active Learning ensures the analyst can effectively contribute to data-driven decision-making and drive innovation across Samsung's diverse business domains.
Learning Resources
Effective leadership is the most important ingredient for successfully capitalizing on data and analytics. This course covers key concepts for analytical senior managers such as the Delta framework, analytical scorecards, and effectively overcoming data and analytics challenges. This course also provides some key techniques for advancing analytical capabilities across the organization. This course…
In today's data-driven world, understanding and leveraging analytics is essential for every business professional. This course is designed to equip you with the knowledge needed to foster an analytical culture that drives digital transformation in your organization. In this course, you'll learn about the value of analytics literacy, including its benefits for both individuals and organizations. Yo…
Applying analytics to solve business problems and realize business opportunities requires a creative blend of business and technical knowledge, skill, and experience. This course covers key roles, responsibilities, and structures in analytics projects. This course also covers the key subject matter expert activities performed throughout the business analytics development process. This course was d…
Proficiency Levels
Novice
- Describes the role of data analysis in supporting Samsung’s strategic objectives.
- Identifies key data sources and their relevance to Samsung’s business areas.
- Explains basic data validation and cleansing techniques used in ensuring data quality.
- Lists recent trends in AI, IoT, and sustainability that impact data analysis at Samsung.
Intermediate
- Works with a specific data analysis tool to generate reports for a particular business unit.
- Participates in the collection and analysis of data for a specific business function.
- Assists in the preparation of data reports for a specific business unit.
- Uses a specific data analysis tool to generate reports for a particular business unit.
- Performs basic data analysis tasks for a specific business unit.
Advanced ★ Required Level
- Evaluates the effectiveness of existing data models in supporting sustainability initiatives.
- Monitors data quality issues and recommends improvements to enhance decision making accuracy.
- Advises on the impact of different analytical approaches on identifying opportunities in AI or connected devices.
- Designs complex datasets to uncover trends that inform product development or market expansion strategies.
- Trains others on interpreting data findings to provide actionable recommendations for optimizing operational efficiency.
- Oversees cross functional data requests to ensure alignment with Samsung’s strategic objectives.
Expert
- Leads the development of advanced data models that integrate multiple business domains, such as semiconductors and smart home devices.
- Designs predictive analytics solutions to anticipate market shifts and inform strategic planning.
- Establishes new data validation frameworks to support emerging sustainability metrics.
- Develops advanced dashboards that provide real time insights for executive decision making.
- Demonstrates best practices in advanced data analysis techniques.
- Creates cross functional projects to address complex data challenges in product innovation.
Speaking, as a critical skill for the Data Analyst role at Samsung, involves the ability to clearly and effectively communicate complex data insights, trends, and recommendations to diverse audiences, including technical teams, business stakeholders, and leadership. This skill requires tailoring messages to align with the audience's level of expertise, ensuring that data-driven findings are both accessible and actionable. Proficiency in speaking also encompasses facilitating discussions, presenting analytical outcomes persuasively, and fostering collaboration across cross-functional teams to drive innovation and strategic decision-making. Strong speaking abilities enable the Data Analyst to bridge the gap between technical analysis and business objectives, supporting Samsung's mission to "Inspire the World, Create the Future" through impactful communication.
Learning Resources
Beyond tools and techniques, business analysts must rely on a strong set of personal skills to be effective in their work. These underlying competencies enable analysts to think critically, collaborate with stakeholders, and communicate clearly across diverse audiences. In this course, explore the personal skills essential to successful business analysis, including analytical thinking, systems and…
Data is meaningful only when information is extracted from it. That information can tell a story, and the best data analysts are magnificent storytellers. But no matter how accomplished a data analyst, a story can't be told compellingly without visualizing what the data says and a key part of a data analyst's role is in reporting on what the data is saying. In this course, you will explore data vi…
The effective use of analytics tools and techniques is a key requirement when analyzing the business problems your organization is currently dealing with. However, it's vital that you also possess a strong set of personal skills to help you process and understand the large amounts of data you'll likely come across during your analysis. In this course, you'll learn about some of the personal compet…
Proficiency Levels
Novice
- Describes the basic structure of a clear and concise verbal data summary.
- Explains the significance of communicating data driven insights to support Samsung’s mission and strategic objectives.
- Identifies key terminology and concepts related to data analysis and effective verbal communication within Samsung’s business context.
- Lists the standard formats and expectations for presenting data findings in meetings at Samsung.
Intermediate
- Works with others to present routine data findings using clear and accessible language.
- Participates in team meetings by verbally summarizing progress on assigned data analysis tasks.
- Assists in communicating the results of standard data validation and cleansing activities to relevant stakeholders.
- Uses prepared talking points to explain basic trends identified in consumer electronics or semiconductor data.
- Explains straightforward data models or dashboards to colleagues.
Advanced ★ Required Level
- Evaluates the effectiveness of different communication approaches when presenting analytical outcomes to diverse audiences.
- Monitors discussions to interpret complex data trends and their implications for business performance.
- Advises on feedback from stakeholders to refine how data insights are verbally communicated for maximum impact.
- Designs meetings where conflicting interpretations of data arise, ensuring clarity and consensus.
- Trains on the clarity and persuasiveness of spoken recommendations during project debriefs.
- Oversees verbal presentations to address challenging questions or skepticism from leadership or technical experts.
Expert
- Leads cross functional workshops to collaboratively interpret data and generate innovative business solutions.
- Designs and delivers compelling presentations that synthesize advanced analytical findings for executive leadership.
- Establishes best practices for verbal communication of data insights within the data analytics function.
- Develops new frameworks for communicating complex data insights to non technical stakeholders across Samsung’s global teams.
- Demonstrates effective speaking techniques for presenting data analysis outcomes.
- Creates persuasive narratives that connect data driven recommendations to Samsung’s strategic goals, such as sustainability or AI leadership.
Active Listening is the ability to fully engage with and comprehend verbal and non-verbal communication, ensuring a clear understanding of the speaker's message, intent, and context. For a Data Analyst at Samsung, this skill is critical in collaborating effectively with cross-functional teams, capturing nuanced requirements, and identifying key insights during discussions. By practicing active listening, the analyst can foster stronger relationships, clarify complex data needs, and contribute to actionable recommendations that align with Samsung's mission to drive innovation and achieve strategic objectives. This skill also supports the analyst in navigating diverse perspectives and ensuring alignment across teams working on cutting-edge technologies and sustainability initiatives.
Learning Resources
Listening is one of the most important ways to ensure effective communication, yet it gets the least focus in a workplace. Listening plays a vital role in any collaborative environment because being able to listen well helps you understand other peoples' perspectives. In this course, you'll learn how to adopt some established best practices for more-focused and committed listening. You'll discover…
The working world has never been more complex than it is today, with cost pressures, customer demands, and competitive markets. None of these challenges can be addressed by "going it alone." Collaboration is key, bringing the organization's best minds together to address these challenges. And key to collaboration is effective listening, ensuring that each member of an organization fully expresses …
Beyond tools and techniques, business analysts must rely on a strong set of personal skills to be effective in their work. These underlying competencies enable analysts to think critically, collaborate with stakeholders, and communicate clearly across diverse audiences. In this course, explore the personal skills essential to successful business analysis, including analytical thinking, systems and…
Proficiency Levels
Novice
- Describes the role of active listening in accurately capturing business needs for data modeling.
- Identifies key terms and concepts related to active listening in the context of data analysis discussions.
- Lists common barriers to effective listening that may impact data quality and communication.
- Explains the importance of clarifying questions when receiving instructions from cross functional partners.
Intermediate
- Uses active listening techniques to ensure accurate interpretation of instructions for data validation and cleansing activities.
- Participates in regular meetings with business units to accurately capture data needs.
- Performs paraphrasing of stakeholder requests to confirm understanding before proceeding with data analysis tasks.
- Assists in resolving ambiguities in data requirements during project kick offs by asking clarifying questions.
- Works to respond appropriately to feedback from team members by acknowledging their perspectives in data solution discussions.
Advanced ★ Required Level
- Evaluates the alignment between stakeholder expectations and delivered data models by reflecting on listening practices.
- Monitors the effectiveness of communication in cross functional meetings by identifying gaps in understanding that impact data solutions.
- Advises on the root causes of miscommunication in collaborative analytics projects and recommends corrective actions.
- Designs feedback mechanisms from project teams to identify recurring misunderstandings and propose improvements in listening approaches.
- Trains others to interpret complex or conflicting requirements by synthesizing input from multiple stakeholders during data project planning.
- Oversees meeting outcomes to ensure all key insights and requirements were accurately captured through active listening.
Expert
- Leads initiatives to integrate active listening into onboarding and training programs for new data analysts.
- Designs and implements structured listening frameworks for data requirements gathering sessions across business units.
- Establishes feedback loops that encourage open dialogue and continuous improvement in listening practices within analytics teams.
- Develops best practice guidelines for active listening tailored to Samsung’s cross functional data analysis environment.
- Demonstrates effective active listening behaviors to improve team collaboration on analytics initiatives.
- Creates new approaches for capturing nuanced business needs by integrating advanced listening techniques into project workflows.
Writing, as a skill for a Data Analyst at Samsung, involves the ability to clearly and effectively communicate complex data insights, trends, and recommendations to diverse audiences, including technical teams and business stakeholders. This skill requires proficiency in crafting concise, data-driven reports, presentations, and visual narratives that align with Samsung's mission to "Inspire the World, Create the Future." Strong writing skills enable the analyst to translate analytical findings into actionable strategies that support innovation and decision-making across areas such as consumer electronics, semiconductors, and connected devices. Additionally, writing must reflect a deep understanding of Samsung's strategic objectives, ensuring that all communication drives alignment with goals like sustainability, AI development, and market leadership.
Learning Resources
For many professionals in the pharmaceutical, technology, finance, and similar industries, technical writing skills are an important part of day-to-day communication. Writing well in these industries isn't just a matter of writing grammatically correct sentences; it also involves producing technical documents that are suited to the requirements, comprehension level, and background of their readers…
Data is meaningful only when information is extracted from it. That information can tell a story, and the best data analysts are magnificent storytellers. But no matter how accomplished a data analyst, a story can't be told compellingly without visualizing what the data says and a key part of a data analyst's role is in reporting on what the data is saying. In this course, you will explore data vi…
Beyond tools and techniques, business analysts must rely on a strong set of personal skills to be effective in their work. These underlying competencies enable analysts to think critically, collaborate with stakeholders, and communicate clearly across diverse audiences. In this course, explore the personal skills essential to successful business analysis, including analytical thinking, systems and…
Proficiency Levels
Novice
- Describes the purpose and audience for different types of written data communications within Samsung.
- Identifies key data terminology and reporting formats commonly used at Samsung.
- Explains the process for documenting data validation and cleansing activities in written form.
- Lists the structure and components of standard data reports and dashboards.
Intermediate
- Works with others to draft clear and concise summaries of routine data analyses for internal team updates.
- Participates in preparing basic written reports that communicate data trends to business stakeholders.
- Assists in composing explanatory notes for data models and dashboards to support user understanding.
- Uses standard operating procedures to document data collection and processing steps in a format accessible to cross functional teams.
- Performs routine data validation and cleansing activities.
Advanced ★ Required Level
- Evaluates the effectiveness of written reports and dashboards in communicating insights to diverse audiences.
- Monitors the impact of written communication on decision making in cross functional projects.
- Advises on synthesizing complex data findings into actionable written recommendations for business leaders.
- Designs processes to analyze feedback from stakeholders to enhance the quality and relevance of written data communications.
- Trains others on editing and refining technical documentation to ensure clarity and alignment with Samsung’s strategic objectives.
- Oversees the narrative flow of data driven presentations for executive audiences.
Expert
- Leads the creation of cross functional communication strategies for sharing complex data insights organization wide.
- Designs comprehensive written reports that integrate advanced analytics to support innovation in product development.
- Develops templates and guidelines for data storytelling that align with Samsung’s mission and brand voice.
- Creates executive summaries that translate technical findings into strategic business recommendations.
- Establishes a system for documenting and sharing best practices in data analysis and reporting.
- Demonstrates the impact of data driven strategies on sustainability or AI initiatives through white papers or case studies.
Operating System Administration involves managing and maintaining the functionality, security, and performance of operating systems to ensure seamless data analysis processes. For a Data Analyst at Samsung, this skill is critical in configuring and optimizing system environments to handle large-scale datasets efficiently, supporting advanced analytical techniques. Proficiency in this area enables the analyst to troubleshoot system issues, implement updates, and ensure compatibility with analytical tools and software, aligning with Samsung's focus on innovation and operational excellence. This expertise contributes to the organization's ability to leverage data-driven insights for strategic decision-making and achieving its objectives in sustainability, AI development, and market leadership.
Learning Resources
Operating systems (OSs) provide a solid foundation for various IT roles, including system administration, networking, cybersecurity, software development, cloud computing, and technical support. In this course, explore the foundations of operating systems, including essential concepts and hands-on installation and configuration techniques for Windows, Linux, and macOS operating systems. Next, lear…
Managing the Analysis Services server helps ensure it runs smoothly and is secure. Explore SSAS management tasks, including security issues, and preparing, backing up, and restoring multidimensional databases.
There are many key utilities and approaches Windows System Admins can take to ensure a well-optimized, fast, and smooth computing experience in Windows 11. In this course, you will explore the term 'maintenance' in the context of a Windows system and learn the importance of performing regular and ongoing maintenance of Windows 11 systems. Next, discover the benefits of the Disk Cleanup utility and…
Proficiency Levels
Novice
- Describes the basic functions and components of operating systems relevant to data processing and analytics.
- Identifies the primary operating systems used for data analysis within Samsung’s technology environment.
- Lists common troubleshooting steps for resolving basic operating system issues encountered during data analysis.
- Explains the importance of operating system compatibility with data analysis software and tools.
Intermediate
- Performs routine operating system updates and patches to maintain secure and stable data analysis environments.
- Configures user permissions and access controls to protect sensitive data used in analytics projects.
- Sets up and manages file systems and storage solutions to support efficient data collection and processing.
- Installs and configures analytical software and tools on designated operating systems for cross functional teams.
- Monitors system performance and resource utilization during standard data processing tasks.
Advanced ★ Required Level
- Evaluates the effectiveness of current operating system configurations in supporting advanced analytical techniques.
- Monitors system logs and performance metrics to identify patterns or bottlenecks affecting data processing efficiency.
- Advises on improvements to operating system administration practices to enhance data quality and operational reliability.
- Designs solutions to complex operating system issues that impact the integrity or performance of large scale data analysis.
- Trains others on assessing the compatibility of new analytical tools or updates with existing operating system environments.
- Oversees the evaluation of security risks and implementation of mitigation strategies for data environments.
Expert
- Leads the integration of new operating system features or technologies to support innovative analytics initiatives.
- Designs and implements optimized operating system environments tailored for high volume, real time data analytics projects.
- Establishes best practices for operating system administration that align with Samsung’s sustainability and innovation goals.
- Develops automated scripts or workflows to streamline system maintenance and data validation processes.
- Demonstrates advanced problem solving skills in resolving complex system issues that impact data analytics performance.
- Creates documentation and training materials for cross functional teams on advanced operating system administration techniques.
Managing Application Deployment involves overseeing the seamless implementation and integration of analytical tools, software, and platforms critical to data-driven decision-making at Samsung. This skill requires expertise in configuring, testing, and deploying applications within complex technological ecosystems, ensuring compatibility with existing systems and alignment with organizational objectives. For a Data Analyst, this includes deploying data visualization tools, machine learning models, and analytics platforms to support strategic initiatives in areas such as consumer electronics, semiconductors, and connected devices. Effective application deployment ensures that analytical solutions are operational, scalable, and capable of delivering actionable insights that drive innovation and enhance operational efficiency.
Learning Resources
Explore a variety of new data science tools available today; the different uses for these tools; and the benefits and challenges in deploying them in this 12-video course. First, examine a data science platform, the nucleus of technologies used to perform data science tasks. You will then explore the analysis process to inspect, clean, transform, and model data. Next, the course surveys integratin…
Cloud-based applications have now become a norm due to zero upfront costs and ease of management. Deployment of cloud-based applications can get a digital product to a wide market without the need to purchase costly server equipment and hire hardware professionals. Use this course to learn about the characteristics of cloud-ready applications and the different concepts, tools, and techniques relat…
Application deployment strategies are vital for Google Professional DevOps Engineers to ensure seamless, efficient, and reliable software releases. Google Cloud Platform (GCP) users who are proficient in deploying and managing applications can leverage its diverse range of deployment models and strategies to achieve optimal scalability, reliability, and availability for their applications, enablin…
Proficiency Levels
Novice
- Describes the basic steps involved in deploying a data visualization tool for business reporting.
- Identifies the key types of analytical applications and tools used within Samsung’s data analytics environment.
- Explains the significance of ensuring data quality and integrity during the deployment of analytics solutions.
- Lists standard procedures for validating and cleansing data prior to application deployment.
Intermediate
- Works with a specific data processing tool to support routine reporting requirements.
- Participates in the integration of a new data visualization application with existing data sources.
- Assists in the deployment of a standard analytics dashboard for a specific business unit.
- Performs basic testing of deployed applications to ensure correct data flow and output.
- Follows data validation and cleansing routines during the deployment of a new analytics platform.
Advanced ★ Required Level
- Evaluates the effectiveness of deployed analytical applications in meeting business requirements for a cross functional project.
- Monitors deployment outcomes to identify and resolve compatibility issues between new analytics tools and legacy systems.
- Advises on the scalability and performance of deployed machine learning models in supporting strategic initiatives.
- Designs and implements data integration processes to enhance the reliability of deployed applications.
- Trains others on diagnosing and troubleshooting complex deployment issues impacting data quality or operational efficiency.
- Oversees improvements to deployment workflows based on analysis of user feedback and system performance metrics.
Expert
- Leads the deployment of complex analytics platforms to support advanced AI driven insights for new product lines.
- Designs automated deployment pipelines to streamline the integration of data models and visualization tools across business units.
- Establishes comprehensive deployment documentation and training materials for cross functional teams.
- Develops new methods for ensuring seamless application deployment in Samsung’s evolving technology ecosystem.
- Demonstrates expertise in configuring and rolling out analytics solutions that support sustainability and environmental impact tracking.
- Creates deployment strategies that align with Samsung’s strategic objectives in collaboration with IT and business leaders.
Web Application Frameworks are essential for Data Analysts at Samsung to efficiently build, deploy, and manage data-driven tools and dashboards that support strategic decision-making. Proficiency in frameworks such as Django, Flask, or React enables seamless integration of analytical models and visualizations into user-friendly web interfaces, fostering collaboration across cross-functional teams. This skill ensures the creation of scalable, secure, and responsive applications that align with Samsung's focus on innovation in consumer electronics, semiconductors, and connected devices. By leveraging these frameworks, Data Analysts can enhance operational efficiency and contribute to achieving Samsung's strategic objectives, including sustainability, AI development, and market leadership.
Learning Resources
This 9-video course explores the concept of web frameworks and how they can speed up development of web applications, and examines the Django framework, a widely used framework written in the Python language. Learners begin by studying fundamentals of web requests, the steps and software required when processing web requests for static and dynamic websites. This leads into examining tasks involved…
For full-stack web developers, frameworks like web2py help you construct all of the business logic and get the wiring and the app details right. When it comes to app appearance and aesthetics, it's wise to rely on powerful frameworks like Bootstrap. Bootstrap helps you build sophisticated user interfaces (UIs) using design templates that incorporate both CSS and JavaScript code for typography, for…
Programming frameworks facilitate software development in a variety of ways. Pre-packaged tooling, improving security, and providing infrastructure are some ways programming frameworks help developers. Through this course, learn about development frameworks, software development best practices, and version control systems. Explore common web frameworks for front-end and back-end development and th…
Proficiency Levels
Novice
- Describes the basic structure of a web application and its role in data visualization and reporting.
- Explains the importance of security, scalability, and responsiveness in web based data tools.
- Identifies the core components and functions of common web application frameworks like Django, Flask, and React.
- Names key terminology related to web application frameworks, including models, views, controllers, and templates.
Intermediate ★ Required Level
- Works with a specific web application framework to develop a simple dashboard for a business unit.
- Participates in the development of a web application to visualize operational data for a specific business unit.
- Assists in the implementation of user authentication in a web application to ensure secure access to sensitive data reports.
- Uses a web application framework to automate the generation of routine data reports for a cross functional project.
- Performs basic customization of a pre built dashboard template to reflect Samsung’s branding and display relevant KPIs.
Advanced
- Evaluates the effectiveness of different web application frameworks for supporting advanced data analytics and visualization needs.
- Monitors and analyzes user feedback and usage data to identify areas for improvement in existing web based data tools.
- Advises on diagnosing and resolving performance bottlenecks in a deployed web application handling large datasets.
- Designs processes to assess the security and compliance of web applications used for sharing sensitive business insights.
- Trains others on comparing the scalability of various frameworks when supporting real time data updates for operational dashboards.
- Oversees the review and optimization of the integration of analytical models within web applications to enhance decision making processes.
Expert
- Leads the creation of an interactive dashboard platform that integrates data from multiple business units and external sources.
- Designs and develops a custom web application framework solution to support advanced analytics for a new product launch.
- Develops innovative features within a web application to enable predictive analytics and scenario modeling for strategic planning.
- Establishes a scalable, secure, and responsive web application infrastructure to support Samsung’s sustainability data initiatives.
- Demonstrates expertise in collaborating with IT and business stakeholders to design user centric web interfaces that drive adoption of data driven tools.
- Creates prototypes and iterates on new visualization modules within a web application to support AI and IoT data analysis.