Business Analytics with Tableau

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.

Recap what you've learned about describing data, then turn to the numbers businesses actually track—and the goals behind them.

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 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.

Recap what you can now do with cells and references, then start putting them to work—cleaning messy data and building the formulas that answer real questions

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.

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.

Look back at everything you've learned—from describing raw data to building metrics, analyzing them in spreadsheets, and communicating what you found—and get oriented to the project ahead.

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.

Get introduced to the core ideas behind effective data visualization, including design principles, common chart types, and how visuals support storytelling with data.

Learn how to choose the right visualizations for exploring data or communicating insights, from histograms to time series to side-by-side bar charts.

Apply design principles to make your data visualizations clear, effective, and trustworthy.

Use color, shape, and size to highlight patterns, emphasize insights, and support accessible data communication.

Review the key ideas behind effective data visualizations and reflect on how principles like chart selection and clarity support strong data storytelling.

Get started with Tableau by installing the software, connecting to datasets, and preparing your workspace for analysis.

Learn how to build and save your first Tableau visualizations using dimensions, measures, and calculated fields.

Recap how Tableau organizes data and visualizations, including key components like rows, columns, and calculated fields, as you reflect on your first experience using the tool.

Get a preview of essential Tableau features—like marks, filters, and chart types—that will support deeper exploration and more advanced visualizations.

Learn how to control aggregation and granularity in Tableau to create more insightful visualizations.

Build interactive visualizations by drilling into custom and automatic hierarchies in Tableau.

Use marks and filters in Tableau to focus your visuals and highlight insights.

Build a range of effective chart types in Tableau and customize them for clarity and impact.

Create custom metrics and dynamic data groupings in Tableau using calculated fields, table calculations, groups, and sets.

Recap the essential Tableau concepts, including marks, filters, chart types, hierarchies, and grouping—reinforcing your understanding before applying them to dashboards and stories.

Explore how dashboards and stories can bring multiple views of your data together, setting the stage for interactivity, deeper analysis, and compelling communication in Tableau.

Build and customize dashboards in Tableau to bring together key charts, metrics, and layout elements for data storytelling.

Build engaging dashboards with filters, highlights, mobile layouts, and intentional design that guides decision-making.

Learn how to guide an audience through your insights with explanatory dashboards and Tableau Stories that communicate data clearly and persuasively.

Reflect on how interactive dashboards and stories can enhance your data communication and prepare you to apply your Tableau skills with purpose and clarity.