Predicting sales with multivariate time series forecasting - Qlik Cloud

Learn how to generate, deploy, and visualize machine learning predictions in Qlik Cloud using the built-in ML experiment and prediction workflow. This step-by-step tutorial walks through the complete process — from uploading your data to building a multivariate time series forecasting model, deploying it, generating predictions, and visualizing the results in an analytics app. You will learn how to: - Upload and prepare training datasets - Build an ML experiment for time series forecasting - Configure grouping fields, future features, and forecast settings - Train and compare models using Qlik AutoML - Deploy the best model and activate it - Prepare & transform apply data using scripting - Generate prediction datasets and monitor progress - Visualize forecasted values inside a Qlik Sense app Perfect for users exploring predictive analytics, data science workflows, and automated forecasting within Qlik Cloud. 🚀 00:00 – Intro 📂 00:06 – Uploading data & creating the experiment ⚙️ 00:37 – Configuring the model 🤖 01:32 – Training & evaluating models 📤 02:15 – Deploying the model 🛠️ 02:47 – Preparing apply data (script) 📈 03:33 – Generating predictions 📊 04:03 – Visualizing prediction results 🏁 04:40 – Conclusion