Business Analytics with Power BI

Discover what data is, where it shows up in everyday life, and why understanding it can help you make smarter decisions across any industry.

Interpret tabular data by identifying what’s being measured, understanding how it’s organized, and recognizing the role of metadata in adding context.

Distinguish between different data types—like numerical vs. categorical—and apply the right reasoning based on how the data is structured and measured.

Summarize datasets using frequencies, measures of center and spread, and descriptive statistics like five-number summaries and tables.

Explore how values relate using ratios, proportions, and correlations to compare parts and measure connections between variables.

Wrap up your introduction to data by reviewing key takeaways about structure, types, summaries, and relationships—building confidence for your next steps in analysis.

Get introduced to five major categories of business metrics and explore how companies measure progress toward common goals like growth, efficiency, and innovation.

Discover how KPIs track business goals and support strategic decisions through clear, measurable indicators across different departments.

Explore common growth metrics like revenue growth rate, market share, and active users—and learn how to calculate, interpret, and apply them to track business expansion.

Explore how time, cost, and resource-based metrics help evaluate and improve a company’s operational efficiency.

Understand how gross margin, net earnings, EBITDA, and CLV reveal how well a business turns revenue into profit.

Evaluate customer happiness and loyalty using metrics like CSAT, churn rate, and repeat purchase rate.

Track how a business develops and adopts new ideas using metrics like product output, adoption rates, and R&D investment.

Learn how to read and interpret the income statement, cash flow statement, and balance sheet to assess a company’s profitability, liquidity, and overall financial health.

Wrap up your understanding of business metrics with a recap of KPI categories, goal types, and the financial statements that help companies track performance across the board.

Get introduced to the history and power of spreadsheets, explore their core features, and see why they’re essential tools for data analysis—no matter which application you choose to use.

Get comfortable navigating spreadsheet interfaces, using menus, toolbars, and shortcuts to organize data and perform key operations efficiently.

Master the use of cell references in spreadsheets, including relative vs. absolute references and named ranges, to write clearer formulas and manage data across sheets.

Perform essential spreadsheet operations like sorting, filtering, copying, and deleting to keep your data clean, organized, and ready for analysis or presentation.

Wrap up your introduction to spreadsheets by reinforcing key concepts like cells, rows, and columns—plus gain confidence in building, editing, and saving your own spreadsheets.

Get oriented to the process of analyzing data in spreadsheets, from cleaning messy inputs to asking meaningful questions that turn raw information into actionable insight.

Build and troubleshoot formulas that calculate values, manipulate text, and combine cell references to clean and analyze spreadsheet data.

Apply logic and condition-based calculations using functions like IF, AND, and COUNTIFS to filter, aggregate, and clean spreadsheet data based on custom rules.

Work with dates and clean tabular data using spreadsheet tools for extraction, validation, deduplication, and text splitting to prepare datasets for analysis.

Retrieve reference data and summarize large datasets using lookup functions and pivot tables for efficient spreadsheet analysis.

Wrap up your journey through spreadsheet data analysis by reviewing key techniques for cleaning, transforming, and querying data—all in service of answering real-world questions.

Explore how charts can bring your data to life. This overview sets the stage for creating pie charts, bar charts, line graphs, and more—so you can spot trends and communicate clearly.

Understand when pie charts work best for showing part-to-whole comparisons and recognize common pitfalls that make them less effective.

Create and format pie charts in spreadsheets to highlight how categories contribute to a whole, adjusting labels, formatting, and layout for clear and accurate presentation.

Interpret and choose between bar and column charts to compare categorical data, understanding when to use grouped or stacked formats to highlight relationships and category differences.

Create and customize bar and column charts in spreadsheets to compare categories, format axes and labels for clarity, and display grouped or stacked layouts for multi-dimensional data.

Understand how line and area charts reveal trends over time, compare categories, and represent parts of a whole, while recognizing when these chart types are appropriate or potentially misleading.

Create and customize line and area charts in spreadsheets to visualize trends, compare series, and highlight data patterns with clear formatting and multiple data series.

Interpret scatter plots to explore relationships between two numerical variables, assess correlation strength and direction, and spot clusters, trends, or outliers.

Create and customize scatter plots in spreadsheets to reveal patterns, spot outliers, and explore potential correlations between two numerical variables.

Learn how values are distributed across ranges, estimate variability, and spot outliers using histograms to interpret the shape and spread of numerical data.

Create and customize histogram charts in spreadsheets to visualize how numerical data is distributed, spot frequency patterns, and identify variability or outliers.

Choose the right chart type for your data and refine its design to clearly communicate trends, comparisons, and distributions to your audience.

Wrap up your charting journey by reinforcing key takeaways—from choosing the right chart type to formatting it for clarity and impact—all using spreadsheet tools.

An Introduction to the course and using the Parch & Posey sales database to solve real-world business questions.

Explore SQL basics, its importance for data analysis, business use cases, database structure, and an overview of popular SQL databases with hands-on practice.

Learn how to interpret Entity Relationship Diagrams (ERDs) to visualize tables, columns, and relationships in a relational database.

Learn SQL basics by understanding key statements like SELECT and FROM, practicing queries, and following best practices for formatting and execution in a SQL workspace environment.

Learn how to use the LIMIT clause in SQL to restrict the number of rows returned in query results, making data exploration faster and more manageable.

Learn to use the SQL ORDER BY clause to sort query results by one or multiple columns, in ascending or descending order, with practical query exercises and solutions.

Learn to use the SQL WHERE clause to filter table data based on numeric or text conditions, using operators like =, !=, >, <, and practice with real-world queries.

Learn how to use arithmetic operators in SQL to create derived columns, perform calculations in queries, and apply order of operations for accurate results.

Learn how to use SQL's LIKE and IN operators to filter text and numeric data efficiently, enabling flexible database queries with wildcards and value lists.

Learn to use AND and BETWEEN operators in SQL to filter data with multiple conditions and ranges, practicing queries on real tables and understanding inclusivity of endpoints.

Learn how to use SQL's NOT and OR operators to filter data, combine conditions, and query for records that do not or do match given criteria, with practical examples and exercises.

Review key SQL commands, syntax, and concepts such as SELECT, FROM, WHERE, ORDER BY, LIKE, and data structure. Reinforce skills to write and understand basic SQL queries.

Gain an understanding of the definition of JOINS and database normalization and learn why they are needed.

Learn how to use INNER JOINs in SQL to combine data from multiple tables, write JOIN queries, and specify columns from different tables using the ON clause.

Learn how to use INNER, LEFT, and RIGHT JOINs in SQL to combine data from multiple tables, including filtering joins and understanding NULLs in join results.

Explore advanced SQL JOINs, primary and foreign keys, multi-table joins, and aliases to efficiently combine and analyze relational database tables.

Recap key concepts learned in this lesson.

An overview of the content that will be learned in Lesson 3.

Learn how NULLs represent missing data in SQL, how they differ from zeros, and how to identify or exclude them using IS NULL or IS NOT NULL in queries and aggregations.

Learn how to use SQL's COUNT function to count rows, understand the difference between COUNT(*) and COUNT(column), and see how NULL values affect results.

Learn how to use the SQL SUM function to total numeric columns, handle NULL values, and perform aggregations across data for inventory analysis and sales calculations.

Learn to use SQL's MIN, MAX, and AVG aggregate functions to find minimums, maximums, and averages, while understanding their handling of NULLs and practical business applications.

Learn how to use GROUP BY in SQL to aggregate data within subsets, group by multiple columns, and combine GROUP BY with ORDER BY for insightful data analysis.

Learn how to use DISTINCT in SQL SELECT statements to retrieve unique rows across specified columns, with practical examples and exercises for real-world query scenarios.

Learn how to use the SQL HAVING clause to filter aggregated group results, enabling analysis of grouped data with aggregate functions beyond the WHERE clause.

Explore how to use SQL date functions like DATE_TRUNC and DATE_PART to analyze, aggregate, and group data by various date parts for effective reporting.

Learn to use SQL CASE statements for conditional logic in SELECT queries, including multi-case logic, handling NULLs, and combining CASE with aggregations.

Learn the basics of SQL subqueries, focusing on scalar subqueries, to simplify complex logic and compare values efficiently within a single query.

Learn how to use subqueries in the WHERE clause to filter SQL results dynamically, making queries more flexible and readable. Practice building both scalar and filtering subqueries.

Learn how to use subqueries in the FROM clause to create derived tables, transform data, and build complex SQL queries efficiently with practical examples.

Learn how Common Table Expressions (CTEs) make complex SQL queries cleaner, more readable, and efficient by organizing logic into reusable, easily-managed parts with the WITH clause.

Discover how temporary tables in SQL simplify complex queries by storing intermediate results, boosting performance, organizing logic, and supporting efficient data analysis.

Learn key tips for writing clean, efficient SQL using subqueries, CTEs, and temp tables, plus best practices for clarity, performance, and maintainability.

Discover SQL window functions to perform calculations like totals, averages, and ranking across rows while retaining individual data for advanced analysis.

Discover how SQL's PARTITION BY enables advanced analytics—like running totals, rankings, and trend analysis—across groups without losing row-level detail.

Understand the role of ORDER BY in SQL window functions for ordering, ranking, and framing data, including ROWS vs RANGE and practical uses like running totals and moving averages.

Learn how to build SQL window functions for detailed analysis, cumulative totals, and efficient queries using PARTITION BY, ORDER BY, and smart optimization strategies.

Learn why data cleaning is crucial, how to identify issues like duplicates, nulls, and outliers, and practical SQL techniques to ensure analysis is accurate and reliable.

Learn essential SQL data cleaning skills: handle missing values, remove duplicates, standardize text, and fix data types for accurate, reliable analysis.

Learn advanced SQL data cleaning using staging tables and workflows for scalable, reliable data prep, with best practices for consistency, deduplication, and quality control.

An introduction to the author and the Power BI course.

In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI

Explore Power BI's core functions: interface, data ingestion, building reports, and the distinction between reports and dashboards for effective data analysis.

Learn Power BI dashboard design basics: choose effective visuals, create clear layouts, apply accessibility, and guide users with interactivity for impactful, user-friendly reports.

Learn how to import, prepare data, and create your first interactive report in Power BI using visuals like line and donut charts for effective project tracking.

Learn to identify and fix Power BI report design issues by applying best practices in layout, visuals, color, and user-focused enhancements for clear, actionable dashboards.

A review of the concepts learned to this point in the course.

An introduction to Power Query and DAX in Power BI.

Learn Power BI Power Query basics: connect, load, clean, and transform data for analysis using practical tools and steps to prepare well-structured datasets.

Discover DAX basics in Power BI—write measures and columns, use core functions, and unlock dynamic analytics for interactive, insightful reports.

Explore DAX in Power BI to prep, model, and visualize data; grasp calculated columns, measures, DAX context, and create dynamic maps and gauges for actionable insights.

Discover Power BI data modeling essentials: star schema, relationships, data cleaning, best practices, and troubleshooting for scalable, insightful reports.

A review of data preparation in Power BI: connect to data, transform with Power Query, build effective models, and use DAX for analysis.

Discover the core chart types in Power BI, how to choose the right visual, and group data for effective, clear, and actionable reports.

Learn to use bar and column charts in Power BI to compare categories, visualize demographic and segmented data, and enhance insights with colors and interactive cross-filtering.

Learn how to use trend charts in Power BI to visualize time-based data, track trends, compare series, and choose the right chart type for clear analysis.

Learn how distribution charts like scatterplots and histograms reveal data patterns, relationships, and variability, and how to create and use them in Power BI for analysis.

Learn to build and compare composition charts like doughnut and column charts in Power BI to visualize how individual categories contribute to a whole and interpret data breakdowns effectively.

Discover how relationship charts like scatter and bubble plots in Power BI help visualize and analyze correlations and patterns between multiple numerical variables.

Learn to build effective Power BI dashboards by creating and customizing charts, applying design best practices, and avoiding common visualization mistakes using real-world requirements.

Discover Power BI's built-in AI features—like Key Influencers and Decomposition Tree—that help users easily gain insights and analyze data using advanced, accessible tools.

Review key Power BI chart types and design best practices to create clear, impactful visuals that help users quickly interpret and communicate data insights.

Discover how to make Power BI dashboards interactive using slicers, filters, and drill features, enabling users to explore, analyze, and gain actionable insights from data.

Discover how to use filters and slicers in Power BI to focus, explore, and interact with data, making reports more dynamic, user-friendly, and insightful.

Learn to use hierarchies and drill-down features in Power BI for data exploration, efficient navigation, and creating interactive, user-friendly dashboards and reports.

Gain a few final tips to create useful reports and dashboards in Power BI using best practices.