Data Analysis involves the ability to collect, process, and interpret complex datasets to uncover meaningful insights and trends that drive informed decision-making. This skill requires proficiency in statistical techniques, data visualization tools, and analytical frameworks to identify opportunities, solve problems, and support strategic objectives. At MHV, Data Analysis is essential for aligning insights with the organization’s mission of empowering members and improving financial well-being, enabling actionable recommendations that enhance operational efficiency, support digital transformation, and strengthen community engagement. This skill also plays a critical role in maintaining a competitive edge in the financial services industry by leveraging data to optimize business strategies and deliver superior member satisfaction.
Learning Resources
Data Analysis is a primary method for deriving valuable insight from raw and unstructured data. The appropriate application of data analysis techniques is vital in deriving only the relevant insight and factual knowledge from available data. Picking the correct data distribution or visualization technique can become critical to the overall data analysis results. Using this course, become familiar …
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 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 reports and dashboards used at MHV.
- Identifies and defines key data sources used in MHV’s financial services operations.
- Lists common data visualization tools and their primary functions within the organization.
- Explains MHV’s data quality and security standards and their importance.
Intermediate
- Works with basic data analysis tools and techniques to support business operations.
- Follows established procedures to collect, organize, and maintain data.
- Uses data visualization tools to create basic charts and graphs for internal presentations.
- Assists in generating routine reports and responding to straightforward data requests.
- Participates in data cleaning activities to ensure accuracy and integrity.
Advanced ★ Required Level
- Monitors the quality and reliability of data sources before integrating them into reports.
- Advises on the interpretation of complex datasets to provide actionable insights for improving member satisfaction.
- Designs methods to evaluate the effectiveness of recent digital banking initiatives using multi source data.
- Oversees the review and validation of dashboards tracking key performance indicators.
- Trains others on how to analyze trends in member account activity to identify emerging patterns or anomalies.
- Evaluates stakeholder data needs and refines analytical approaches accordingly.
Expert
- Leads the design and implementation of new data models to support strategic initiatives such as digital transformation.
- Creates advanced dashboards that integrate multiple data streams for executive decision making.
- Establishes innovative analytical frameworks to measure the impact of community engagement programs.
- Leads cross functional projects to enhance data driven operational efficiency.
- Designs customized reporting solutions to address unique business challenges faced by MHV.
- Develops and documents best practices for data analysis tailored to MHV’s environment.
Proficiency in SQL (Structured Query Language) is essential for the Data Analyst role at MHV, enabling the efficient extraction, manipulation, and analysis of data from relational databases. This skill allows the analyst to write complex queries to retrieve and aggregate data, ensuring accurate and actionable insights that support data-driven decision-making across the organization. SQL expertise is critical for identifying trends, optimizing operational processes, and contributing to strategic initiatives such as digital transformation and enhanced member satisfaction. Mastery of this programming language ensures the ability to handle large datasets effectively, aligning with MHV’s mission to empower members and improve financial well-being.
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.
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 …
Databases cannot perform at all without data - it is that simple. Data is the lifeblood of databases, and once a database is populated with data, the things a data analyst can do with it are truly remarkable. By harnessing the power of data, modern life has become more efficient in virtually every way. In this course, you will explore the basics of data, beginning with an introduction to data type…
Proficiency Levels
Novice
- Describes the basic structure of MHV’s relational databases used for member and transaction data.
- Lists the primary data sources and systems used by MHV for collecting and storing business and member data.
- Explains how SQL queries support the generation of standard reports for operational and compliance needs.
- Identifies common SQL commands and explains their functions in the context of financial data analysis.
Intermediate ★ Required Level
- Uses SQL to extract and manipulate data for routine reports and dashboards.
- Performs basic SQL joins to combine data from multiple tables.
- Follows standard procedures to validate data accuracy and completeness.
- Works with SQL filters to segment data for targeted analysis.
- Assists in fulfilling ad hoc data requests from business units.
Advanced
- Monitors the effectiveness of digital banking initiatives by evaluating usage data extracted via SQL.
- Designs and runs SQL scripts that detect anomalies or inconsistencies in large datasets.
- Advises on the impact of community engagement programs by querying and comparing relevant member participation data.
- Oversees the development of complex SQL queries to identify trends in member behavior, such as changes in product adoption over time.
- Evaluates the retention and satisfaction of new members versus long term members using SQL to perform cohort analysis.
- Trains others to interpret SQL query results to provide actionable recommendations for improving operational efficiency or member experience.
Expert
- Leads the integration of new data sources into MHV’s data warehouse using advanced SQL techniques.
- Designs and implements advanced SQL based data models to support new business intelligence dashboards for executive decision making.
- Establishes best practices for SQL development and data management across the organization.
- Develops automated SQL scripts to streamline the generation of recurring reports for compliance and performance tracking.
- Demonstrates expertise in optimizing complex SQL queries for performance and scalability.
- Creates custom SQL procedures to support predictive analytics initiatives, such as forecasting loan demand or member attrition.
Proficiency in Python is essential for the Data Analyst role at MHV, enabling the efficient manipulation, analysis, and visualization of complex datasets to uncover actionable insights. This skill involves expertise in using Python libraries such as Pandas, NumPy, and Matplotlib to process large volumes of data, identify trends, and generate reports that support data-driven decision-making. Python’s versatility also facilitates the automation of repetitive tasks, enhancing operational efficiency and enabling the analyst to focus on strategic initiatives like digital transformation and community engagement. Mastery of Python ensures the ability to deliver high-quality, data-backed recommendations that align with MHV’s mission of empowering members and improving financial well-being.
Learning Resources
This 12-video Skillsoft Aspire course uses Python, the preferred programming language for data science, to explore data in Pandas with popular chart types such as the bar graph, histogram, pie chart, and box plot. Discover how to work with time series and string data in data sets. Pandas represents data in a tabular format which makes it easy to perform data manipulation, cleaning, and data explor…
Python is a powerful programming language for data science, and pandas is a popular open-source data manipulation and analysis library in Python. Combined with prompt engineering techniques, working with data in Python is easy and intuitive, which allows you to be more productive and efficient. You will start this course by leveraging prompt engineering to work with pandas. You will explore librar…
Data Analysis is a primary method for deriving valuable insight from raw and unstructured data. The appropriate application of data analysis techniques is vital in deriving only the relevant insight and factual knowledge from available data. Picking the correct data distribution or visualization technique can become critical to the overall data analysis results. Using this course, become familiar …
Proficiency Levels
Novice
- Describes the primary Python libraries used for data analysis in financial services.
- Explains how Python can be used to ensure data quality and integrity in member account datasets.
- Lists the steps for importing, cleaning, and exporting data using Python in the context of MHV’s operations.
- Names basic Python syntax and data structures relevant to processing credit union data.
Intermediate
- Uses Python to import, clean, and preprocess member transaction data for routine reporting.
- Develops basic Python scripts to automate the generation of monthly dashboards tracking account growth and loan performance.
- Applies Python functions to validate and correct data inconsistencies in savings and checking account records.
- Utilizes Python to create simple visualizations (e.g., bar charts, line graphs) illustrating trends in member engagement.
- Implements Python based routines to extract and summarize data for internal stakeholders’ recurring information requests.
Advanced ★ Required Level
- Evaluates the effectiveness of digital banking initiatives by comparing pre and post implementation data using Python analytics.
- Monitors the impact of new financial products by analyzing adoption rates and usage patterns with Python.
- Advises on the interpretation of Python generated reports to provide actionable recommendations for improving member satisfaction.
- Designs Python scripts to segment members based on financial behavior, supporting targeted community engagement strategies.
- Trains others on how to assess data quality and integrity, identifying anomalies or potential security risks in transaction records using Python.
- Oversees the analysis of complex datasets using Python to identify emerging trends in loan applications and member demographics.
Expert
- Leads the development of Python tools that enable cross functional teams to access and visualize key performance metrics.
- Designs and implements advanced Python based data models that forecast membership growth and asset trends.
- Creates automated Python workflows that streamline the reporting process for regulatory compliance.
- Develops custom Python dashboards that integrate real time data feeds for executive decision making.
- Demonstrates expertise in using Python to solve complex financial data challenges.
- Establishes best practices for Python based data analysis in the financial sector.
The skill of Dashboard creation and utilization involves designing, developing, and maintaining visually intuitive and interactive dashboards that effectively communicate complex data insights to diverse stakeholders. For the Data Analyst role at MHV, this skill is essential for transforming raw data into actionable visual representations that support data-driven decision-making across the organization. Proficiency in this skill ensures the ability to highlight key performance indicators, trends, and opportunities aligned with MHV’s strategic objectives, such as digital transformation and enhancing member satisfaction. A strong command of dashboard tools and techniques enables the Data Analyst to collaborate with teams, streamline reporting processes, and provide clear, impactful insights that drive operational efficiency and strategic growth.
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…
Explore the role played by dashboards in data exploration and deep analytics in this 11-video course. Dashboards are especially useful in visualizing data for a wide variety of business users, so that they can better understand the data being analyzed. First, learners examine the essential patterns of dashboard design and how to implement appropriate dashboards by using Kibana, Tableau, and Qlikvi…
Proficiency Levels
Novice
- Describes the basic principles of data visualization and dashboard design for credit union reporting.
- Identifies the primary components and functions of dashboards used in financial services at MHV.
- Explains how dashboards support decision making and align with MHV’s mission and strategic objectives.
- Lists the data sources commonly integrated into dashboards at MHV.
Intermediate
- Uses standard templates to build simple dashboards for routine operational metrics.
- Follows data security and privacy standards when handling dashboard data.
- Performs data filtering and sorting to address specific business questions.
- Participates in updating dashboards with new data to reflect current trends.
- Works on populating dashboards with accurate data from validated sources.
Advanced ★ Required Level
- Monitors dashboard data to identify emerging trends and anomalies in member behavior or financial performance.
- Evaluates the effectiveness of current dashboards in meeting the needs of different departments at MHV.
- Advises on dashboard insights to provide actionable recommendations for improving operational efficiency.
- Oversees data integrity and troubleshoot discrepancies or inconsistencies in dashboard outputs.
- Designs dashboard performance metrics against organizational benchmarks and strategic goals.
- Trains stakeholders to refine dashboard content based on feedback and evolving business needs.
Expert
- Leads the design and development of advanced, interactive dashboards tailored to support MHV’s digital transformation initiatives.
- Establishes dashboard standards and best practices to ensure consistency and usability across MHV.
- Develops automated dashboard reporting processes to streamline information delivery across the organization.
- Creates visualizations that clearly communicate complex data insights to both technical and non technical audiences.
- Demonstrates expertise in integrating multiple data sources to create comprehensive dashboards that provide holistic views of member engagement.
- Designs customized dashboards for specific projects, such as community engagement or new product launches.
Power BI is a critical skill for the Data Analyst role at MHV, enabling the creation of dynamic, visually compelling dashboards and reports that translate complex datasets into actionable insights. This skill involves proficiency in data modeling, visualization, and the use of Power BI’s advanced analytics features to identify trends and opportunities that align with MHV’s mission of empowering members and improving financial well-being. Expertise in Power BI supports collaboration across teams by delivering clear, data-driven recommendations that enhance operational efficiency and drive strategic initiatives such as digital transformation and community engagement. Mastery of this tool ensures the ability to effectively communicate data insights, contributing to superior member satisfaction and sustained organizational growth.
Learning Resources
Microsoft Power BI is a powerful and versatile visualization technology widely used in data analytics, especially business data analysis. Business analysts can use this service to build and publish interactive reports for executive audiences as well as collaborators. Get your head around the specifics of data visualization in this introductory course. Explore different types of visualizations and …
Business intelligence (BI) has become a cornerstone for organizations aiming to make data-driven decisions, and Power BI is one of the leading tools in the BI space. In this course, explore foundational BI concepts and discover how to install and configure Power BI for effective data analysis. Next, learn how to transform raw data into actionable insights by creating visually compelling reports an…
Most businesses have an enormous amount of data in their possession. But this data is only as valuable as the quality of the processes used to understand it. So how do you gather seemingly disparate data from multiple sources and turn it into digestible insights for all to use? One way to do this is to use Power BI, Microsoft's business analytics service. Use this course to comprehend exactly what…
Proficiency Levels
Novice
- Describes the process for importing data into Power BI from MHV’s core banking systems and other sources.
- Identifies the basic components and interface elements of Power BI, including dashboards, reports, and data sources relevant to MHV’s financial services.
- Explains the importance of data quality, integrity, and security in the context of Power BI reporting for a credit union.
- Cites key performance indicators (KPIs) tracked by MHV and how they are represented in Power BI dashboards.
Intermediate
- Uses Power BI to create basic reports and dashboards for routine financial operations.
- Follows MHV’s data standards to prepare datasets for analysis in Power BI.
- Shares Power BI reports with team members to support collaborative decision making.
- Works with Power BI’s built in visualization tools to present standard financial education metrics.
- Participates in routine monthly performance reviews using Power BI to filter and sort data.
Advanced ★ Required Level
- Monitors the accuracy of complex data models in Power BI to ensure reliable reporting for regulatory compliance.
- Advises on the effectiveness of recent digital banking initiatives by comparing pre and post implementation KPIs in Power BI.
- Designs Power BI dashboards to assess the impact of community engagement programs by visualizing participation and outcome data.
- Oversees the identification of data anomalies or inconsistencies in loan application data and recommends corrective actions.
- Evaluates member transaction patterns in Power BI to identify emerging trends and present findings to support new product development.
- Trains business stakeholders to interpret Power BI analytics and refine operational strategies based on data driven insights.
Expert
- Leads the creation of interactive Power BI reports that enable executives to explore financial trends and make informed decisions.
- Designs advanced Power BI dashboards that integrate multiple data sources to provide a holistic view of member satisfaction and operational efficiency.
- Develops custom Power BI data models to support strategic initiatives such as targeted marketing campaigns or new product launches.
- Demonstrates new visualization techniques in Power BI to communicate complex financial concepts to non technical stakeholders.
- Creates automated recurring data analysis processes in Power BI to improve reporting efficiency and reduce manual effort.
- Establishes best practices for Power BI report design and data governance tailored to MHV’s organizational needs.
Proficiency in Tableau is essential for the Data Analyst role at MHV, enabling the creation of dynamic, visually compelling dashboards and reports that translate complex datasets into actionable insights. This skill involves leveraging Tableau’s advanced data visualization and analytical capabilities to identify trends, monitor key performance indicators, and support strategic decision-making aligned with MHV’s mission of empowering members and enhancing financial well-being. Expertise in Tableau ensures the ability to effectively communicate data-driven recommendations to diverse teams, fostering collaboration and driving initiatives such as digital transformation and operational efficiency. Mastery of this tool contributes to MHV’s objectives of sustained growth, superior member satisfaction, and maintaining a competitive edge in the financial services industry.
Learning Resources
Generally speaking, the ultimate goal of analyzing data is to be able to communicate any interesting relationships that you have found. In this 10-video course, learners will discover how Tableau's analysis tools can further data analysis and communicate those relationships. Share your findings by observing how to create dashboards with interactive tools and exploring data. Begin by using Explain …
Tableau is a data visualization tool suitable for a variety of purposes and situations. Knowing the basics of this tool will help you share necessary data with stakeholders and peers in a meaningful and engaging way. This course will introduce you to Tableau's basic features and cover the fundamental operations performed with this tool. You'll start by loading data into Tableau using a variety of …
To become a data science expert, you must master the art of data visualization. This 12-video course explores how to create and use real time dashboards with Tableau. Begin with an introduction to real-time dashboards and differences between real time and streaming data. Next, take a look at different cloud data sources. Learn how to build a dashboard in Tableau and update it in real time. Discove…
Proficiency Levels
Novice
- Describes the basic components and interface elements of Tableau relevant to MHV’s data environment.
- Explains the purpose of dashboards and reports in supporting MHV’s financial services operations.
- Identifies common data sources used by MHV and how to connect them to Tableau.
- Lists key performance indicators (KPIs) tracked by MHV and their significance to member satisfaction.
Intermediate
- Uses Tableau to create basic dashboards and reports for internal use.
- Follows MHV’s data governance standards when importing and displaying sensitive member information in Tableau.
- Works with Tableau to generate routine reports that track loan performance and deposit growth for internal teams.
- Assists in updating existing Tableau dashboards with new data to ensure accurate and timely reporting.
- Participates in sharing Tableau visualizations with stakeholders to support regular decision making processes.
Advanced ★ Required Level
- Evaluates the effectiveness of current dashboards in meeting the needs of MHV’s digital transformation initiatives.
- Monitors data quality issues in Tableau visualizations and proposes solutions to enhance accuracy.
- Advises on the interpretation of complex data relationships in Tableau to provide actionable insights for community engagement programs.
- Designs Tableau dashboards to compare performance metrics across branches and recommend operational improvements.
- Trains others on how to analyze member transaction data in Tableau to identify emerging trends impacting financial well being.
- Oversees the refinement of Tableau reports based on feedback and evolving business needs.
Expert
- Leads the creation of custom Tableau templates for recurring reports tailored to MHV’s business objectives.
- Designs advanced Tableau dashboards that integrate multiple data sources to support strategic initiatives.
- Develops interactive Tableau visualizations that enable real time monitoring of key financial indicators.
- Creates automated Tableau workflows that streamline reporting for compliance and regulatory requirements.
- Establishes best practices for Tableau dashboard design to ensure consistency across the organization.
- Demonstrates innovative ways to visualize member engagement data in Tableau to inform outreach strategies.
Data Science is the ability to extract meaningful insights and actionable intelligence from complex datasets through advanced analytical techniques, statistical modeling, and machine learning. This skill involves proficiency in data manipulation, visualization, and interpretation to identify trends, patterns, and opportunities that drive strategic decision-making. For the Data Analyst role at MHV, Data Science expertise is essential for supporting initiatives like digital transformation, operational efficiency, and community engagement, ensuring alignment with the organization’s mission of empowering members and enhancing financial well-being. Mastery of this skill enables the development of data-driven recommendations that contribute to sustained growth, superior member satisfaction, and a competitive edge in the financial services industry.
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 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…
Data mining and data science are rapidly transforming decision-making business practices. For these activities to be worthwhile, raw data needs to be transformed into insights relevant to your business's goals. In this course, you'll walk through each stage of the data mining pipeline covering all requirements for reaching a conclusive and relevant business decision. You'll examine data preparatio…
Proficiency Levels
Novice
- Describes the basic structure and purpose of data models, reports, and dashboards used to track credit union performance.
- Lists common analytical tools and software used by the Data Analyst team at MHV, such as Excel, SQL, and business intelligence platforms.
- Identifies and defines key data science concepts relevant to financial services, such as data cleaning, statistical analysis, and data visualization.
- Explains the role of data science in supporting MHV’s mission to empower members and improve financial well being.
Intermediate
- Uses data extraction tools to collect member transaction data for routine reporting on account activity trends.
- Follows established protocols to securely store and share data reports with relevant stakeholders.
- Performs standard data cleaning techniques to prepare raw datasets for analysis, ensuring accuracy and consistency.
- Assists in generating basic visualizations (e.g., bar charts, line graphs) to illustrate trends in loan applications or member engagement.
- Works to respond to routine data requests from business units by providing summarized insights using predefined templates.
Advanced ★ Required Level
- Evaluates the effectiveness of current data models in predicting loan default risk and recommends improvements.
- Monitors complex datasets to identify emerging trends in member behavior, such as shifts in digital banking usage.
- Advises on data quality issues and proposes solutions to enhance the integrity of member and transaction data.
- Designs data driven insights to support strategic initiatives, such as expanding financial education programs.
- Trains cross functional teams to evaluate the impact of new digital services on member satisfaction.
- Oversees existing dashboards and reports for accuracy, relevance, and alignment with MHV’s strategic objectives.
Expert
- Leads the design and implementation of advanced data models to forecast membership growth and asset trends for strategic planning.
- Creates custom data visualizations to communicate complex insights to non technical stakeholders and executive leadership.
- Develops interactive dashboards that enable real time monitoring of key performance indicators across business units.
- Establishes comprehensive data quality frameworks to proactively identify and address data integrity issues.
- Demonstrates innovative analytical approaches to measure the impact of community engagement initiatives on member retention.
- Designs automated reporting systems to streamline operational efficiency and reduce manual workload.
Data Visualization is the ability to transform complex datasets into clear, compelling visual representations that facilitate understanding and decision-making. This skill involves selecting appropriate visualization techniques, such as charts, graphs, and dashboards, to effectively communicate trends, patterns, and insights to diverse stakeholders. For a Data Analyst at MHV, proficiency in Data Visualization is essential to support data-driven strategies, enhance operational efficiency, and align insights with the organization’s mission of empowering members and improving financial well-being. By presenting data in an accessible and actionable format, this skill enables collaboration across teams and contributes to achieving MHV’s strategic goals, including digital transformation and superior member satisfaction.
Learning Resources
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…
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…
Using data visualizations effectively and correctly is a part of building a data-driven culture in your team. Data visualization creates accessible, understandable, and effective graphic representations of data to help teams understand the patterns and trends in their data and make data-driven decisions. In this course, you will learn about the fundamentals of data visualization, why it is importa…
Proficiency Levels
Novice
- Describes the role of data visualization in communicating trends and patterns to non technical stakeholders.
- Lists the primary data sources within MHV that are commonly visualized for operational and strategic reporting.
- Explains the importance of data visualization in supporting member focused decision making at MHV.
- Identifies and describes common types of data visualizations used in financial services, such as bar charts, line graphs, and pie charts.
Intermediate
- Uses data visualization tools to create basic charts and graphs for internal reports.
- Follows MHV’s data quality standards when preparing visualizations.
- Assists in developing simple dashboards to monitor key performance indicators.
- Works on updating existing dashboards with current data for routine decision making.
- Participates in generating visual summaries of survey results from member satisfaction initiatives.
Advanced ★ Required Level
- Evaluates the effectiveness of current dashboards in supporting digital transformation initiatives and recommends improvements.
- Monitors the impact of visualized data on operational efficiency by soliciting feedback from end users.
- Advises on the best visualization techniques to communicate complex loan portfolio data to stakeholders.
- Designs visualizations that align with MHV’s mission of empowering members and improving financial well being.
- Trains others on how to interpret visualized data to identify potential risks or opportunities in MHV’s financial performance.
- Oversees the analysis of member transaction data to identify emerging trends and visualize these insights for management review.
Expert
- Leads the development of data visualization tools that support strategic decision making across departments.
- Designs innovative visualization templates tailored to the needs of community engagement and financial education programs.
- Establishes visualization standards that enhance data driven culture at MHV.
- Develops advanced visualizations that highlight the impact of new products or services on member financial health.
- Demonstrates best practices for data visualization to ensure consistency and clarity across the organization.
- Creates visual analytics tools that enable real time monitoring of digital banking adoption and member satisfaction.
Statistics is a foundational skill for the Data Analyst role at MHV, enabling the accurate analysis and interpretation of complex datasets to uncover trends, patterns, and actionable insights. This skill involves proficiency in statistical methods, including descriptive and inferential statistics, hypothesis testing, regression analysis, and data modeling, to support data-driven decision-making. At MHV, expertise in statistics is essential for identifying opportunities to enhance operational efficiency, improve member satisfaction, and drive strategic initiatives such as digital transformation and community engagement. A strong command of statistical techniques ensures the ability to deliver precise, reliable insights that align with MHV’s mission of empowering members and fostering financial well-being.
Learning Resources
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…
Statistics is a branch of mathematics that involves the collection, analysis, interpretation, presentation, and organization of data. It provides a framework for making inferences and drawing generalizable conclusions from observed information and it offers great tools to uncover patterns, trends, and relationships within datasets. Begin this course by exploring two important types of statistics -…
Statistical analysis involves making educated guesses known as hypotheses and testing them to see if they hold up. Use this course to learn how to apply hypothesis testing to your data. Examine the use of descriptive statistics to summarize data and inferential statistics to draw conclusions. Learn how population parameters differ from summary statistics and how confidence intervals are used. Disc…
Proficiency Levels
Novice
- Describes the basic concepts and principles of statistical analysis in a credit union context.
- Identifies key statistical tools and techniques used in analyzing credit union data.
- Explains the importance of maintaining data integrity and security in statistical analysis.
- Lists common types of data collected and analyzed at MHV.
Intermediate
- Uses statistical software to generate summary reports on loan approval rates by branch location.
- Performs data validation checks to ensure accuracy before conducting statistical analyses on financial transactions.
- Works with basic descriptive statistics (mean, median, mode, standard deviation) for member account balances to support routine reporting.
- Assists in developing simple data visualizations (e.g., histograms, bar charts) to present trends in member engagement for internal stakeholders.
- Participates in applying regression analysis to predict member attrition based on historical account activity data.
Advanced ★ Required Level
- Evaluates the impact of community engagement initiatives by comparing pre and post program member satisfaction scores using inferential statistics.
- Monitors the reliability and validity of data sources used in operational dashboards, recommending improvements where necessary.
- Advises on multivariate analysis results to provide actionable recommendations for enhancing digital banking adoption.
- Designs complex datasets to identify underlying trends in loan default rates and evaluate the effectiveness of risk mitigation strategies.
- Trains others to critically evaluate the outcomes of A/B testing on new financial products, determining statistical significance and business implications.
- Oversees correlations between member demographics and product usage to inform targeted marketing strategies.
Expert
- Leads the design and implementation of advanced statistical models to forecast membership growth and inform strategic planning.
- Develops custom dashboards that integrate real time statistical analyses for executive decision making.
- Creates data driven frameworks for evaluating the success of new digital transformation initiatives.
- Designs new methods for measuring and reporting on member satisfaction using advanced statistical techniques.
- Establishes comprehensive data quality protocols to ensure statistical analyses meet regulatory and organizational standards.
- Demonstrates best practices for statistical analysis tailored to MHV’s unique data environment and business objectives.
Problem Solving is the ability to approach complex challenges methodically, analyze data-driven insights, and develop effective solutions that align with organizational goals. For a Data Analyst at MHV, this skill involves identifying patterns and trends within large datasets, diagnosing underlying issues, and crafting actionable recommendations to support strategic initiatives such as digital transformation and community engagement. Strong problem-solving ensures the ability to address operational inefficiencies, adapt to evolving market conditions, and contribute to sustained growth and superior member satisfaction. This skill is critical for navigating the dynamic financial services landscape and maintaining MHV’s competitive edge.
Learning Resources
For most business professionals, solving problems is a major part of their jobs. But what are often seen as problems are really symptoms of deeper challenges. Treating these symptoms may provide temporary relief, but the deeper issues remain. By investigating the scope of problems and addressing their root causes, you can work toward ultimately finding solutions for sustained success. In this cour…
Almost any business problem can have more than one solution, but some solutions are better than others. And one of those will be the best solution. Trying to find the best, right solution to a business problem can itself be a problem. Finding that right solution means applying the right process and methods to meet your organization's needs now, and in the future. In this course, you'll explore app…
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 process for collecting and processing member data in compliance with MHV standards.
- Identifies and defines key data sources used in MHV’s financial services operations.
- Explains the importance of data security and privacy in the context of member information.
- Lists the primary key performance indicators (KPIs) tracked in MHV’s dashboards and reports.
Intermediate
- Works with data models to support business reviews and operational meetings.
- Participates in data validation to ensure accuracy in member and transaction datasets.
- Assists in generating standard reports and dashboards to monitor trends in account activity.
- Uses established procedures to collect and process operational data for routine reporting.
- Follows best practices to maintain data security and confidentiality during analysis.
Advanced ★ Required Level
- Evaluates the effectiveness of current data models and recommends improvements to enhance reporting accuracy.
- Monitors transaction and member data to identify emerging trends or anomalies impacting service delivery.
- Advises on actionable solutions to address root causes of data inconsistencies.
- Designs dashboards to ensure they effectively communicate key insights to stakeholders.
- Trains others on interpreting complex datasets and providing insights for strategic projects.
- Oversees the impact of digital banking initiatives by interpreting usage data and member feedback.
Expert
- Leads the development of new data models and analytical frameworks to support digital transformation initiatives.
- Designs innovative dashboards and visualization tools tailored to the needs of different business units.
- Establishes predictive analytics solutions to anticipate member needs and improve satisfaction.
- Develops comprehensive data quality protocols to proactively address integrity and security challenges.
- Demonstrates best practices for advanced data analysis within the organization.
- Creates and manages projects that leverage data insights to optimize operational efficiency.
Detail-oriented skills are essential for the Data Analyst role at MHV, as they enable precise analysis and interpretation of complex datasets to uncover actionable insights. This skill ensures accuracy in identifying trends, validating data integrity, and delivering reliable recommendations that align with MHV’s mission of empowering members and improving financial well-being. A strong attention to detail supports the development of high-quality reports and dashboards, which are critical for driving strategic initiatives such as digital transformation and community engagement. By maintaining meticulous focus, the Data Analyst contributes to operational efficiency, superior member satisfaction, and the organization’s competitive positioning in the financial services industry.
Learning Resources
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…
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…
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 use of a specific data field in a core banking system.
- Explains the steps required to access and retrieve a specific dataset.
- Identifies a common data quality issue in a member record.
- Lists the key data fields used in a standard report.
Intermediate
- Works with basic data entry and validation tasks for routine financial reports.
- Uses established templates to generate basic dashboards for member engagement metrics.
- Follows data security protocols when handling sensitive member information.
- Performs routine checks to ensure data consistency across multiple sources and systems.
- Assists team members by providing clear, detailed documentation of data sources and methodologies.
Advanced ★ Required Level
- Evaluates the accuracy and reliability of data models used to forecast membership growth or loan performance.
- Monitors and analyzes complex datasets to identify emerging trends in member behavior or product usage.
- Advises on the impact of data quality issues on the effectiveness of digital banking initiatives.
- Designs and implements processes to investigate discrepancies in financial or operational data, determining root causes and recommending corrective actions.
- Trains others on reviewing and refining reporting processes to improve the precision and clarity of insights delivered to stakeholders.
- Oversees collaboration with cross functional teams to interpret data findings and validate assumptions underlying business recommendations.
Expert
- Leads the development of innovative reporting solutions that support MHV’s digital transformation and community engagement goals.
- Designs and implements new data validation frameworks to proactively detect and prevent errors in critical datasets.
- Establishes advanced dashboards that integrate multiple data sources to provide comprehensive views of key performance indicators.
- Develops detailed documentation and training materials to standardize data quality practices across the organization.
- Demonstrates the ability to construct custom data models to support strategic decision making for new product launches or member outreach programs.
- Creates and manages projects to enhance data integrity and reporting accuracy in collaboration with IT and business units.
Decision Making involves the ability to evaluate complex datasets, identify key patterns, and make informed, data-driven recommendations that align with organizational goals. For a Data Analyst at MHV, this skill is critical in supporting strategic initiatives such as digital transformation, operational efficiency, and community engagement. Effective decision-making requires balancing analytical rigor with an understanding of MHV’s mission to empower members and improve financial well-being, ensuring that insights lead to actionable outcomes. This skill also entails collaborating with cross-functional teams to prioritize initiatives and drive sustained growth, superior member satisfaction, and competitive advantage in the financial services industry.
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 …
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…
Data mining and data science are rapidly transforming decision-making business practices. For these activities to be worthwhile, raw data needs to be transformed into insights relevant to your business's goals. In this course, you'll walk through each stage of the data mining pipeline covering all requirements for reaching a conclusive and relevant business decision. You'll examine data preparatio…
Proficiency Levels
Novice
- Describes the basic process for collecting and processing data within the credit union environment.
- Explains the importance of data security and privacy in financial services.
- Lists the primary key performance indicators (KPIs) tracked by MHV.
- Names common data quality issues and basic methods for ensuring data integrity.
Intermediate
- Uses established data models to generate routine reports for business and operational teams.
- Follows best practices to ensure data security when handling member information.
- Participates in team projects by applying data analysis techniques to answer straightforward business questions.
- Performs standard procedures to clean and validate datasets before analysis.
- Works with dashboards to monitor and report on daily or weekly trends in member activity.
Advanced ★ Required Level
- Monitors the effectiveness of data models and recommends improvements based on findings.
- Advises on the impact of digital transformation initiatives on member engagement.
- Designs processes to assess data quality and integrity, proposing corrective actions for identified gaps.
- Oversees the prioritization of data analysis projects based on alignment with MHV’s strategic objectives and stakeholder needs.
- Evaluates complex datasets to identify emerging trends affecting member satisfaction or operational efficiency.
- Trains others on collaborating with cross functional teams to diagnose root causes of performance issues using data driven insights.
Expert
- Leads the development of new data models and dashboards to support evolving business strategies and digital initiatives.
- Designs innovative methods for integrating disparate data sources to enhance insight generation.
- Establishes advanced analytics solutions that inform community engagement and financial education programs.
- Develops protocols for ongoing data quality monitoring and improvement across the organization.
- Demonstrates frameworks for evaluating the success of new products or services using data driven metrics.
- Creates and guides cross departmental projects that leverage data analysis to drive operational improvements.
Research is the ability to systematically gather, evaluate, and synthesize information from diverse sources to uncover insights and inform decision-making. For a Data Analyst at MHV, this skill involves identifying relevant data points, exploring industry trends, and leveraging both internal and external datasets to support strategic initiatives such as digital transformation and community engagement. Effective research ensures the analyst can provide accurate, actionable recommendations that align with MHV’s mission of empowering members and improving financial well-being. This skill is critical for maintaining a competitive edge in the financial services industry and driving data-driven strategies that enhance operational efficiency and member satisfaction.
Learning Resources
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…
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…
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…
Proficiency Levels
Novice
- Describes the key financial products and services offered by MHV and their associated data points.
- Explains the importance of data quality and security in the context of financial services research.
- Identifies and lists the primary internal data sources used for member account analysis at MHV.
- Lists common industry terms and trends relevant to credit unions and digital banking.
Intermediate
- Works with basic data analysis tools and techniques to support a specific business function.
- Participates in the collection and analysis of data to support a specific business function.
- Uses established methods to gather and organize data to support a specific business function.
- Performs basic data validation techniques to ensure accuracy in a specific business function.
- Assists in the preparation of reports to support a specific business function.
Advanced ★ Required Level
- Evaluates the impact of community engagement initiatives by synthesizing internal and external data sources.
- Monitors the quality and reliability of third party data before integrating it into MHV’s reporting systems.
- Advises on complex datasets to provide actionable recommendations for improving member satisfaction.
- Designs methods to compare and contrast MHV’s performance metrics with industry benchmarks to identify growth opportunities.
- Trains others to investigate anomalies in financial data and determine their root causes through systematic research.
- Oversees the analysis of member transaction data to identify patterns and evaluate the effectiveness of recent digital banking enhancements.
Expert
- Leads the development of new research methodologies to assess the impact of digital transformation initiatives on member experience.
- Designs innovative data models that integrate external market trends with internal member data to inform strategic planning.
- Establishes new methods for tracking and visualizing the impact of financial education programs on member outcomes.
- Develops comprehensive reports that synthesize research findings for executive decision making.
- Demonstrates the ability to initiate and manage cross functional research projects to explore opportunities for operational efficiency.
- Creates protocols for ongoing competitor analysis to proactively identify market shifts relevant to MHV.
Proficiency in Microsoft Excel is essential for the Data Analyst role at MHV, enabling the effective organization, analysis, and visualization of complex datasets. This skill includes advanced knowledge of Excel functions such as pivot tables, VLOOKUP, conditional formatting, and data validation, as well as the ability to create dynamic dashboards and automate processes using macros. Expertise in Excel supports the identification of trends and actionable insights, aligning with MHV’s mission to empower members and improve financial well-being. Additionally, this skill facilitates collaboration across teams by presenting data in clear, impactful formats that drive strategic decision-making and operational efficiency.
Learning Resources
Analyze data efficiently using Excel 2013. Discover how to work with PivotTables, including formatting, sorting, filtering, grouping, and using slicers. In addition, explore how to insert, modify, and analyze using PivotCharts.
Excel 365 offers a variety of advanced functions for data management and formula creation. In this course, discover how to build formulas to find information in tables, work with data arrays, and obtain date-related information. First, enhance your data management and analysis skills with powerful lookup functions such as VLOOKUP, HLOOKUP, and the newly introduced XLOOKUP. These tools are crucial …
Excel is not only used for aggregating and analyzing data, but also for data cleansing. There are several data cleaning, validation, and checking techniques available, some of which are among Excel's most well-known and widely-used functions. In this course, you'll start by using various string and data manipulation functions to clean data and fill in missing values. Next, you'll perform simple da…
Proficiency Levels
Novice
- Describes the purpose of using Excel to analyze financial data.
- Explains the process of importing data from core banking systems into Excel.
- Identifies the steps to create simple charts and graphs to visualize trends in member transactions.
- Lists the key Excel functions such as SUM, AVERAGE, and COUNT relevant to financial data analysis.
Intermediate
- Uses Excel to create and maintain reports for a specific function or department.
- Performs basic data analysis using Excel formulas and functions.
- Follows established procedures to ensure data accuracy and integrity in Excel reports.
- Assists in the development of Excel templates for routine reporting needs.
- Participates in the creation of dashboards using Excel to track key performance indicators.
Advanced ★ Required Level
- Evaluates the effectiveness of Excel based data analysis processes and recommends improvements.
- Monitors the use of advanced Excel functions to ensure compliance with organizational standards.
- Advises on the use of Excel for complex data analysis and reporting tasks.
- Designs Excel based dashboards to track key performance indicators.
- Trains others in the use of advanced Excel features for data analysis and reporting.
- Oversees the development of Excel based models to support business decision making.
Expert
- Leads the development of Excel based solutions for complex data analysis and reporting needs.
- Designs Excel models that integrate with other software applications for comprehensive data analysis.
- Establishes best practices for Excel use across the organization to ensure consistency and accuracy.
- Develops advanced Excel tools that automate complex data processing tasks.
- Demonstrates expertise in using Excel to solve complex business problems.
- Creates Excel dashboards that provide real time insights into key business metrics.
Computer Science expertise is essential for the Data Analyst role at MHV, encompassing a strong foundation in computational principles, data structures, algorithms, and programming languages. This skill enables the analyst to efficiently process, analyze, and interpret large datasets, leveraging tools and technologies to uncover actionable insights that drive strategic decision-making. Proficiency in computer science supports the development and optimization of data models, automation of workflows, and integration of advanced analytics techniques, aligning with MHV’s focus on digital transformation and operational efficiency. By applying computer science knowledge, the analyst contributes to enhancing member satisfaction, improving financial well-being, and maintaining MHV’s competitive edge in the financial services industry.
Learning Resources
Big data analytics, collecting vast amounts of data and transforming it into insights, drives major business decisions everywhere. Managers, decision-makers, data technicians, and data enthusiasts alike benefit from knowing how various systems and technologies are used in big data projects. Use this course to progress from a foundational comprehension of big data analytics to grasping more advance…
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…
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…
Proficiency Levels
Novice
- Describes the basic concepts of computer science and their relevance to data analysis in financial services.
- Explains the role of computer science in supporting digital transformation and operational efficiency at MHV.
- Lists the primary data sources and systems used in MHV's digital banking and financial operations.
- Documents standard data security and integrity protocols followed by MHV to protect member information.
Intermediate
- Uses SQL or Python to extract and process data for routine reporting.
- Develops and updates basic data models and dashboards to track key performance indicators.
- Applies standard data validation techniques to ensure accuracy and integrity of datasets.
- Implements established data security measures when handling sensitive information.
- Utilizes data visualization tools to present routine insights to stakeholders.
Advanced ★ Required Level
- Evaluates the effectiveness of existing data models and recommends improvements to enhance operational efficiency.
- Monitors complex datasets to identify trends and patterns that inform business decisions and member engagement strategies.
- Advises on the impact of digital banking initiatives by interpreting data on member usage and satisfaction.
- Designs solutions to maintain high standards of data integrity and security.
- Trains others on the most effective algorithms or analytical approaches for a given business problem.
- Oversees data driven recommendations for strategic initiatives.
Expert
- Leads the design and implementation of advanced data models and automated workflows to support new digital banking features or services.
- Develops innovative analytics solutions that provide actionable insights for community engagement and financial education programs.
- Creates custom dashboards and reporting tools tailored to the needs of various departments within MHV.
- Establishes new data sources and technologies to enhance the scope and depth of organizational analytics.
- Demonstrates best practices for data processing, analysis, and security in alignment with MHV’s strategic objectives.
- Designs pilot projects that leverage computer science expertise to improve member satisfaction and operational outcomes.
Effective communication is essential for the Data Analyst role at MHV, enabling the clear and concise presentation of complex data insights to diverse audiences, including non-technical stakeholders. This skill involves the ability to translate analytical findings into actionable recommendations that align with MHV’s mission and strategic objectives, fostering collaboration across teams. Strong communication ensures that data-driven strategies are understood and embraced, supporting initiatives such as digital transformation, operational efficiency, and community engagement. Additionally, it requires active listening and adaptability to address feedback and tailor messaging to the needs of various stakeholders, ultimately driving informed decision-making and organizational success.
Learning Resources
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…
The final step in the data science pipeline is to communicate the results or findings. Explore communication and visualization concepts needed by data scientists.
Proficiency Levels
Novice
- Describes the basic process for collecting, processing, and presenting data insights at MHV.
- Identifies key data terminology and concepts relevant to MHV’s financial products and services.
- Lists the standard formats and channels used at MHV for sharing data insights and recommendations.
- Names the primary audiences for data reports within MHV, including both technical and non technical stakeholders.
Intermediate
- Works with others to present data findings using clear, concise language and standard reporting templates.
- Participates in responding to straightforward data related questions from stakeholders, ensuring clarity and accuracy.
- Assists in translating basic analytical results into simple recommendations aligned with MHV’s operational goals.
- Uses established dashboards to communicate key performance indicators to relevant teams.
- Performs documentation and sharing of data collection and analysis processes with colleagues to support transparency.
Advanced ★ Required Level
- Evaluates the effectiveness of current data communication methods and recommends improvements.
- Monitors the alignment of data driven recommendations with MHV’s mission and strategic initiatives.
- Advises on the quality and relevance of data visualizations used in reports and suggests enhancements.
- Designs processes to interpret complex data trends and explain their implications for MHV’s business strategies to cross functional teams.
- Trains others on facilitating discussions with stakeholders to clarify data needs and refine reporting approaches.
- Oversees the assessment of feedback from non technical audiences to enhance the clarity and impact of data presentations.
Expert
- Leads the development of new communication frameworks for sharing advanced analytics with diverse audiences.
- Designs tailored data storytelling approaches to support digital transformation and community engagement initiatives.
- Establishes workshops to train staff on interpreting and utilizing data insights for decision making.
- Develops innovative reporting tools or dashboards that improve stakeholder understanding and engagement.
- Demonstrates cross departmental collaborations to co create data driven strategies and communication plans.
- Creates guidelines for translating complex analytical findings into actionable recommendations for executive leadership.
Management, as a skill for the Data Analyst role at MHV, involves the ability to effectively organize, prioritize, and oversee data-related projects to ensure alignment with organizational goals. This includes coordinating with cross-functional teams, managing timelines, and ensuring the delivery of actionable insights that support strategic initiatives such as digital transformation and community engagement. Strong management skills enable the Data Analyst to balance competing priorities, foster collaboration, and drive data-driven decision-making that enhances operational efficiency and member satisfaction. This skill is critical for maintaining focus on MHV’s mission of empowering members and achieving sustained growth in a competitive financial services landscape.
Learning Resources
As data and analytics move ever closer to the core of enterprises, it's the contemporary manager's responsibility to both to set an example and to exert their influence to improve business performance and capability through data and analytics. This course covers best practices for encouraging analytics in everyday work, and enabling data and analytics-driven behaviors within the organizational env…
As companies transition to the digital age, it is increasingly essential for decision-makers to utilize the vast amount of data in their systems properly. Proper governance and a working knowledge of data management systems ensure a significant competitive advantage, allowing companies to have more insight into their work and utilize their resources more efficiently. Use this course to familiarize…
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 steps involved in collecting and processing data for analysis.
- Explains the purpose of dashboards and reports in supporting decision making.
- Identifies key data sources used in MHV’s financial services operations.
- Lists the primary stakeholders who rely on data insights within MHV.
Intermediate ★ Required Level
- Works with basic data collection and reporting tools to support routine analyses.
- Follows established procedures to ensure data quality and security in routine tasks.
- Uses MHV’s reporting tools to generate standard dashboards for tracking key metrics.
- Participates in the timely delivery of standard data reports to stakeholders.
- Assists in responding to straightforward data requests using approved processes.
Advanced
- Evaluates the effectiveness of current data models in meeting the needs of different business units.
- Monitors trends in member behavior to identify opportunities for improving financial products.
- Advises on the impact of data driven recommendations on operational efficiency and member satisfaction.
- Designs processes to prioritize multiple data projects based on organizational goals and resource availability.
- Trains others to identify gaps in data quality or integrity and recommend corrective actions.
- Oversees collaboration with cross functional teams to interpret complex datasets and provide actionable insights.
Expert
- Leads the development of advanced dashboards that provide strategic insights for senior leadership.
- Designs and implements new data management processes to support digital transformation initiatives.
- Establishes best practices for cross team collaboration on data driven projects.
- Develops project plans for complex data analysis initiatives aligned with MHV’s strategic objectives.
- Demonstrates innovative methods for integrating data from multiple sources to enhance reporting accuracy.
- Creates frameworks for ongoing evaluation and improvement of data quality and security standards.
Operations as a skill for the Data Analyst role at MHV involves the ability to streamline and optimize processes to enhance organizational efficiency and effectiveness. This includes leveraging data to identify operational bottlenecks, uncover opportunities for improvement, and implement data-driven solutions that align with MHV’s strategic goals, such as digital transformation and superior member satisfaction. The skill requires a strong understanding of operational workflows within the financial services industry, as well as the ability to collaborate across teams to ensure that insights translate into actionable outcomes. By applying this skill, the Data Analyst contributes to sustained growth, improved financial well-being for members, and a competitive edge in the market.
Learning Resources
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…
Dealing with large amounts of data is essential to any modern business and to become a data-driven organization, leaders and decision-makers must establish a deeply ingrained data culture. Use this course to understand the underlying principles of analyzing data and get familiar with terms related to data in order to properly deliver data-related projects. This course will help you identify the ba…
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 basic concepts of operational data and its role in financial services.
- Explains the purpose and use of specific operational reports and dashboards.
- Identifies key data elements and their relevance to MHV’s operational processes.
- Lists common tools and technologies used in operational data management.
Intermediate
- Works with basic data analysis tools to monitor daily operational performance against KPIs.
- Participates in generating standard operational reports and dashboards for internal stakeholders.
- Assists team members by providing routine data insights to address predictable operational questions.
- Uses established data quality checks to ensure accuracy in operational datasets.
- Follows MHV’s best practices for maintaining data security and integrity in operational tasks.
Advanced ★ Required Level
- Evaluates the effectiveness of current operational processes using data driven insights.
- Monitors and interprets trends in operational KPIs to recommend targeted improvements.
- Advises on the impact of new digital tools or process changes on operational performance.
- Designs and implements strategies to address inefficiencies or bottlenecks in service delivery.
- Trains cross functional teams to diagnose root causes of operational issues using data.
- Oversees the accuracy and relevance of operational dashboards and reports.
Expert
- Leads the design and implementation of new data models to optimize operational workflows and reporting.
- Develops innovative dashboards that provide actionable insights for operational decision making.
- Establishes initiatives to automate routine operational data collection and reporting processes.
- Creates frameworks for continuous monitoring and improvement of operational efficiency.
- Demonstrates best practices for operational data analysis tailored to MHV’s needs.
- Designs and manages pilot projects to test new data driven operational strategies.
The skill of Presentations for the Data Analyst role at MHV involves effectively communicating complex data insights and analytical findings to diverse audiences, including non-technical stakeholders and leadership teams. This skill requires the ability to craft clear, compelling, and visually engaging presentations that translate data into actionable recommendations aligned with MHV’s mission and strategic objectives. Strong presentation skills are essential for fostering collaboration, driving informed decision-making, and supporting initiatives such as digital transformation, operational efficiency, and community engagement. Mastery of this skill ensures that data-driven strategies are understood and embraced across the organization, contributing to superior member satisfaction and sustained growth.
Learning Resources
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…
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…
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 clear communication when presenting data insights to support MHV’s mission.
- Identifies key data visualization tools and presentation formats commonly used at MHV.
- Lists common data security and privacy considerations when preparing presentations for internal and external stakeholders.
- Names the primary audiences for data presentations within the credit union, such as leadership and non technical staff.
Intermediate
- Uses standard templates to create visually clear reports for routine meetings.
- Follows established guidelines to ensure data integrity and confidentiality.
- Performs basic presentations summarizing key performance indicators for a specific financial product or service.
- Explains straightforward data findings to a small team, ensuring clarity for non technical members.
- Assists in incorporating simple charts and graphs to illustrate trends in member engagement or product usage.
Advanced ★ Required Level
- Monitors the effectiveness of presentations by gathering feedback and identifying areas for improvement.
- Advises on the impact of data driven recommendations presented to leadership on subsequent business decisions.
- Designs presentations that interpret complex data trends, providing actionable recommendations to improve member satisfaction.
- Oversees the tailoring of presentation content and style to suit different stakeholder groups, such as executives versus frontline staff.
- Evaluates audience engagement during presentations and adjusts delivery methods to enhance understanding.
- Trains others to present comparative analyses of operational efficiency metrics, highlighting opportunities for process improvement.
Expert
- Leads the design and implementation of a new presentation framework that enhances the clarity and impact of data insights for strategic initiatives.
- Designs and leads cross functional workshops to teach best practices in data storytelling and visualization for MHV teams.
- Develops interactive dashboards and dynamic presentation materials that allow stakeholders to explore data in real time.
- Creates customized presentations that integrate multiple data sources to support digital transformation projects.
- Demonstrates innovative ways to visualize complex financial data, making insights more accessible to community partners.
- Establishes guidelines for consistent, high quality presentations across the organization, ensuring alignment with MHV’s mission and values.