The importance of data forecasting needs to be highlighted—its use cases, why we feel the need to dedicate a whole chapter to it, why it's essential in the field of business. Then we will slowly move into using Qlik for data forecasting and lastly, jot down all the activities we shall be carrying out through the course of this chapter.
Organizations must adapt to a constantly changing world. To make those adjustments, its management needs to predict what may happen in the future. Being assertive about making forecasts can mean the difference between being ready to adapt to a new market or new situations.
In the past couple of years, advanced analytics using data science tools has become increasingly important to all organizations because it uses mathematics and statistics to enable more accurate results in data analysis. Now, we are going to see how we can leverage our Qlik Sense analysis, helping our users (or ourselves) to prepare data forecasts.
In this chapter, we will work together to enable the Qlik Sense applications to predict how our business Key Performance Indicator (KPI) will perform in the future. This is not about using technology to predict business behavior, but instead, a matter of using technologies from data science such as machine learning (ML) or forecasting, in order to predict business behavior.
The following topics will be covered in this chapter:
- How to install R and Python onto your computer or server
- How to load the required libraries
- How to configure your Qlik Sense environment to connect to R and Python platforms
- How to use the R and Python modules in your Qlik applications