Association Rules Step by Step using T-SQL, R, Python, Azure ML, and SSAS
Links:
Sign up to our Meetup group https://www.meetup.com/hybrid-virtual...
Join our LinkedIn group / 12487. .
Follow us on Twitter / hybridvug
...and of course don't forget to subscribe to our channel, like the video, and hit the bell! It really helps us in our mission to produce free content for the masses.
Session Details:
Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. In this session, you will learn how to perform Market Basket Analysis using T-SQL, R, Python, Azure ML, and SSAS.
You will learn how to recognize good products, products that increase sales of other products, and toxic products -products that are usually sold alone or are the last product in the basket, thus ending shopping.
In this session, measures like support, confidence, and lift, are explained in detail and will cover sequential basket analysis is as well. We will demonstrate step-by-step demos in T-SQL to demonstrate how calculations are made and also use other languages and other platforms!
Speaker:
Dejan Sarka is a Microsoft MCT and Data Platform MVP. He is an independent consultant, trainer, and developer focusing on database & business intelligence applications. His specialties are advanced topics like data modeling, data mining, and data quality. On these toughest topics, he works and researches together with SolidQ and The Data Quality Institute. He is the founder of the Slovenian SQL Server and .NET Users Group. Dejan Sarka is the main author or co-author of twelve books about databases and SQL Server, with more to come. Dejan Sarka also developed and is developing many courses and seminars for SolidQ, Microsoft and Pluralsight. He is a regular speaker at many conferences worldwide for more than 15 years, including conferences like Microsoft TechEd, PASS Summit,and others.
Host/s:
Mark Broadbent.
Mikael Wedham.
Originally recorded on 6th October 2021.
Video Production: Mark Broadbent 29th November 2021.
00:00 Introduction
02:00 Association Rules - Support
05:12 Association Rules - Confidence
05:12 Association Rules - Lift
05:12 Association Rules - Order
09:46 Demo
48:14 Conclusion
48:31 Questions