In this chapter, we used Qlik Sense to explore the bike sharing dataset. In Qlik Sense, we saw different ways of doing an intuitive correlation analysis.

After this, we created an application to analyze the rental activity. The application had three sheets following the DAR approach.

Finally, we used Rattle to confirm the correlation analysis we did with Qlik Sense, then we created a predictive model to forecast the demand depending on the weather forecast.

With Rattle, we used the variable cnt as the target variable; it would be very interesting to repeat the exercise using the variables registered and casual.

You've arrived at the end of the book, so by now you should understand the basics of predictive analytics and data visualization and have gained some expertise in using Rattle and Qlik Sense Desktop.

Now you can use Qlik Sense to quickly analyze business data. With Qlik Sense you can discover hidden patterns in your data and create powerful visualizations to present the conclusions...