Quick and Easy Time-Series Forecasting in PowerBI: A Practical Guide
How to set up and configure a forecasting system in just a few clicks
Introduction
Time-series forecasting has become a ubiquitous tool for businesses, governments, and individuals alike. It is nowadays being applied in almost every domain imaginable: in finance to predict stocks and interest rates, in healthcare to predict hospital bed capacity, in transportation to plan routes and traffic patterns, in energy to predict power supply and demand, and the list goes on.
Consequently, there exists a need for a user-friendly and easy-to-onboard tool that is quick and seamless to set up. Luckily, PowerBI has got you covered. With their built-in tool, users are able to set up and configure a forecasting system in just a few clicks.
This article will provide you with a step-by-step guide on how to achieve this. But before diving into the practical part, let’s go through the algorithm that’s running under the hood.
The Algorithm: Exponential Smoothing
PowerBI is using exponential smoothing — a robust algorithm capable of capturing trends in time-series data, while at the same time suppressing noise and unwanted variation.
