This 5-part course consists of tutorials on how to learn SQL for Data Analytics. It’s designed to be very hands-on and will walk you through the fundamentals of querying, aggregating, and creating reports. You don’t have to have any knowledge of programming to do this course!
The primary objectives of this course are as follows:
- Learn how to create, query, and modify databases using commands such as Create, Select, Where, Group, Having, Update, Truncate, etc.
- Create relationships between tables using Joins.
- Learn how to aggregate data using mathematical functions and create reports using these aggregates.
- Lean how to write efficient and dynamic queries using case statements, temporary tables, and subqueries.
- Get hands-on practice using SQLFiddle
This tutorial is created for people who want to answer questions using data. Increasingly, SQL is becoming more and more important when analyzing data since it’s used for every aspect from storing to cleaning, accessing, and gaining insights from information already stored in databases. It’s easy to understand and can be used to go through vast amounts of data — this is why it’s used by the world’s largest companies!
- Collect data using standard SQL commands (Create, Update, Truncate, Select, etc.).
- Filter data using advanced SQL commands (Where, Group By, Having, Order By, Distinct, Limit).
- Obtain data by creating relationships between tables using Joins (Inner, outer, union)
- Gather filtered data using SQL Boolean operators (AND and OR) and SQL conditional operators (=, >, <, and BETWEEN).
- Querying Databases in SQL Part 1
- Querying Databases in SQL Part 2
- Write Boolean statements with the IN SQL conditional operators and null functions (“IS NULL,” “IS NOT NULL,” and “IFNULL”).
- Clean data using SQL mathematical functions (ABS, SIGN, MOD, etc.).
- Summarize data sets by employing aggregation functions (“Sum,” “Average,” “Count,” etc.).
- Creating reports by applying aggregation methods.
- Aggregating Data in SQL Part 1
- Aggregating Data in SQL Part 2
- Use CASE statements to structure data and create new attributes.
- Combine multiple subqueries into one using “AS.”
- Temporary Tables and Subqueries.
- Determining data trends through advanced reporting.
- Writing Efficient and Dynamic Queries