Jun 2, 2018

Data Science with TM1 and Planning Analytics

Having accurate data in your TM1 and Planning Analytics application is just one part of the job, the second part which is even more important is to understand your data. This is where Data Science can help. Data Science will help you to improve how you make decisions by better understanding the past and predicting the future.

Combine the best of two worlds

On one side, IBM TM1 and Planning Analytics has been very successful over the years mainly for its strong planning and reporting capabilities and on the other side Python is becoming more and more popular thanks to its unique Data Science eco-system. Now with the free Python package TM1py, you can combine the best of these two worlds.

Open the Python community to TM1/Planning Analytics

TM1py makes it easy to do Data Science such as statistics or time series forecasting with your TM1 and Planning Analytics application by opening the Python community to IBM TM1 and Planning Analytics.

A whole new world of free tools to boost your IBM TM1 and Planning Analytics application.

The Python community is very creative in terms of Data Science, there are lots of free tools for data exploration such as Pandas and Plotly or for timeseries forecasting such as Facebook Prophet. All these packages are free and ready-to-use!

For example, with a few lines of code you can use the Ploty package to build interactive charts:

Do the same things but smarter!

Free-up your time by automating repeated tasks, TM1py will enable you to do things smarter such as uploading daily exchange rates from a webservice or automating your daily forecast by using Facebook Prophet:

A Step-By-Step Guide To Data Science with TM1/Planning Analytics

To see data science with TM1 and Planning Analytics in action, we created a series of three articles which will guide you step by step through your first data science experience. In Part 1, you will load weather data from a web service into your TM1 cube, in Part 2, you will then explore your data using Pandas and Ploty and finally in Part 3, you will use time series forecasting using Facebook Prophet:


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