Learn & Query On
A great team is more than the sum of its parts: some team members will have special aptitudes or skills; their levels of experience will differ. That’s why collaboration among data analysts is so powerful.
Our latest release of Aginity Pro, v34, is now available for both MacOS and Windows. This update includes deeper integration with Amazon Redshift, Cross-Database Autocomplete, and some just-right UI improvements.
We hear it all the time: data engineers and analysts complaining about how hard it is to locate existing SQL assets, whether generated by themselves or by a teammate, for reuse in a new project.
As organizations ingest and process more data, managing this crucial business asset can create insights into just about every aspect of the business: customers, employees, information systems, partners’ performance, marketing efficiency — the list is effectively endless.
Good analytics is equal parts business acumen and technology expertise. Even so, it’s easy to become imbalanced in pursuit of ever-deepening data engineering skills.
Learn how to become a rock star SQL analysts, data engineer or data scientist.
For Data Engineers
Redshift Utilities: Generate DDL and Search Table Metadata
MPP databases require you to figure out how to navigate their system tables. We’ll show you a few examples how to work with system tables to reverse engineer DDL and search for tables using wildcards.
Generating SQL to Profile Table Data
Leveraging what we learned in Lesson 1, we will expand the concept to use system tables and prior scripts to generate code that profiles a Redshift table. Check out this lesson to learn more.
Building a Random Number Generator to Create an Image
Feeling creative? Check out this lesson to learn how to build a random number generator in Redshift and create an image of Aginity’s Enterprise Product Manager George L’Heureux.
For Business Analysts
Rate of Return on Redshift
Internal Rate of Return (IRR) is a calculation frequently used to estimate an investment’s rate of return. Take this lesson to figure out how to use Redshift SQL to perform this calculation..
Create Basic Recency, Frequency and Monetary Segments
RFM (Recency, Frequency, Monetary) analysis is highly used marketing model for behavior based customer segmentation. It groups customers based on their purchase history. Learn how to do this in SQL!