SQL-Powered Excel for Business Analytics

Structured Query Language (SQL) is the primary language used for accessing and managing data in a relational database system. Analysts, project managers, and other professionals want to make informed decisions using large datasets, but without a working knowledge of SQL, they often have to request that IT staff perform these data retrievals.

Expert George Mount walks you through using SQL to query a database to extract the information you need for your analyses. No prior experience in programming or databases is required. As an Excel user, you already know more about these topics than you realize. Over three informative hours, you’ll discover how the foundations of SQL relate to everyday Excel tasks, empowering you to better explore and analyze your own databases.

What you’ll learn and how you can apply it

By the end of this course, you’ll understand:

• The basics of relational databases and SQL’s role
• The foundational commands used for reading data from one or more tables in a database
• Concepts such as schemas, primary keys, and foreign keys (i.e., what makes relational databases “relational”)

And you’ll be able to:

• Use SQL to query a database to extract useful information
• Explore basic SQL commands and functions
• Extract data and work with queries to pull the data you need for your analysis

This course is for you because…

• You’re an analyst, project manager, or other professional working with data.
• You work primarily with Excel and see its limitations for data storage and retrieval.
• You want to work with the larger datasets that are often housed in databases.

Prerequisites

• A machine with SQLite and SQLiteStudio installed
• Basic to intermediate Excel knowledge (sorting and filtering, IF() statements, SUMIF(), COUNTIF(), PivotTables, etc.)

Recommended preparation:

• Read “Why Learn SQL?” and “Databases” (chapters 1 and 2 in Getting Started with SQL)
• Watch the “Excel Tables” and “Pivot Tables” sections of Big Data Analytics with Excel (video, ~2h 30m)

Recommended follow-up:

• Read Learning SQL, second edition (book)
• Read SQL Cookbook (book)