Qlik Predict - Tip #1 - Quick Tips Before You Get Started

In this video, Mike Tarallo from Qlik shares essential tips you should know before using Qlik Predict. Whether you're just getting started with machine learning or looking to better understand predictive analytics in Qlik, these practical insights will help you ask the right questions and prepare your data effectively. Learn how to identify meaningful outcomes, analyze historical data patterns, and set the foundation for building strong machine learning models in Qlik. 00:00 - Introduction Mike Tarallo introduces the topic and what viewers will learn about Qlik Predict in this video. 00:03 - Tip #1: Know Your Predictive Outcome Learn why it's important to define your desired outcomes and questions before starting. Example use case: predicting order cancellations based on historical sales data. 00:20 - Analyzing Historical Data Explore a real-world scenario involving canceled orders, their timing, and what might be causing them, such as employee availability. 00:43 - Formulating Predictive Questions Mike explains how to derive predictive questions like “Will a customer cancel?” and “How many days until cancellation?” to guide your model. 01:00 - Proactive Planning with Predictions Discover how predictions can help you prioritize workflows and potentially reduce cancellations by taking early action. 01:08 - Matching Data to Questions Now that predictive questions are defined, learn how to assess whether your data can support those questions effectively. 01:16 - Tip #2 Preview: Data for Machine Learning A preview of the next tip that focuses on the importance of using appropriate training data for building ML models in Qlik Predict.