Intellicus BI can integrate with different Data Science environments to make your data-driven decision-making more powerful. It can help you generate predictions and perform what-if analysis.
Data Science delves deep into your data, scientifically puts all the correlations into perspective. It creates models or a series of formulas, using the patterns of historical data and uses these patterns to calculate inferences for future. These inferences help you to connect the dots and take informed, futuristic business decisions.
Intellicus provides a seamless connection to popular Data Science environments like R, Python with access to all the available libraries to fulfill your Data Science requirements.
With What-If analysis, business users can analyze the predictions based on various business scenarios. They can play with the quantum of different variables to achieve a desired outcome and make their business strategies accordingly.
Below image shows how Intellicus connects with Python environment and the process it follows to push your data and bring back the predictive insights.
Data Science works as an integrated environment with Intellicus.
To successfully perform data science tasks using Python environment in Intellicus, you need to
- Install Python environment on the same network as Intellicus
- Install intellicuspy, which is a TCP/IP server for executing dynamic Python code from Intellicus
After installing the above components, you need to create connection with Python environment to let Intellicus communicate with it and process your data. You also need to create a file source connection that works as an Exchange File-system to help Intellicus and Python environment transmit data to each other. Both Intellicus and Python environment should have read-write access to this exchange location. We have explained how to form these connections in Connecting to Python Data Science Environment section.
Once you create the required connections, you can add Data Science Engine step while preparing your transforming your data that is while creating a Query Object. When you add a Data Science Engine step, Intellicus BI server performs the initial processing and then transmits the data along with a script (that you can create or add inside Intellicus) to the data science environment for advanced statistical computations. The Python environment based on the script processes your data (performs learning, modelling and brings out predictions) and transmits data back to Intellicus. The processed data can now be used for further transformation steps and/or can be visualized on the Intellicus UI.
With Intellicus you can perform Data Science tasks while reporting as well, referred as Predictive Analytics in the guide. Intellicus gives you numerous intuitive charts to understand and analyze your current and predicted data.
Note: To be able to integrate Data Science environment to Intellicus, you must have the required Data Science environment running parallel to Intellicus on the server. This guide explains the steps to install Python environment on Linux and Windows machines and covers steps to integrate the environment with Intellicus. Intellicus requires you to install ‘intellicuspy’ to be able to run Python with it, the installation and integration steps are detailed in the subsequent chapters. In Intellicus, we have referred Data Science environment as Data Science Engine.
Who can do what
Super administrators and/or users with specific roles and privileges assigned by super administrator can form connections.
Data Scientists or Designers can write Python script and perform transformation steps.
End/Business users can use the data prepared by designers/data scientists to form reports and visualize data with advanced visualizations. They can also perform predictive and what-if analysis while viewing the reports.
Note: You can create or add Python scripts inside Intellicus’ environment.