Data Science with Intellicus - Using R
Intellicus seamlessly integrates with various data science environments, empowering your decision-making with predictive analytics and what-if analysis.
Overview
Data science leverages statistical algorithms, machine learning, and deep learning to analyze historical data, identify hidden patterns, uncover correlations, and generate actionable predictions. These insights help businesses make informed, data-driven decisions with increased confidence.
With Intellicus, you can:
Connect with multiple data science engines
Perform machine learning-based data processing
Use what-if simulations to model business scenarios
Visualize both current and predicted data through interactive dashboards and reports
Data Science Integration Workflow
Intellicus acts as an integrated platform for data science processing. The following high-level steps summarize the data science workflow:
Establish Connections: Connect Intellicus to supported data science engines (e.g., R) and configure a file system for data exchange.
Add Data Science Step: Insert a data science step during Query Object design.
Data Transmission: Intellicus pushes the prepared data and a user-defined script to the data science engine.
Script Execution: The data science engine executes the script (learning and modeling).
Result Retrieval: The processed results are retrieved by Intellicus and made available for visualization or further transformation.
Note
A sample workflow diagram illustrates how Intellicus interacts with external data science engines. Refer to the figure in the UI for details.
Connecting to Data Science Engines
To integrate a data science engine:
Create a Data Science Engine Connection in Intellicus.
Create a File Source Connection that serves as the exchange location for data and scripts.
Ensure both Intellicus and the data science engine have read/write access to this shared location.
Refer to the Creating Connections section for detailed configuration steps.
Adding a Data Science Step
Once connections are established:
Navigate to Design > Query Object.
Add a Data Science step after initial data preparation.
Write your script (e.g., in R) directly within Intellicus using the built-in editor.
The Intellicus BI Server transmits data and script to the engine, receives the processed output, and continues with the next transformation or visualization steps.
Intellicus supports full scripting capability for statistical modeling, learning, and predictions. You can also define variables for what-if simulations.
What-If Analysis
Business users can leverage what-if analysis to simulate various scenarios by adjusting input parameters. This helps:
Visualize how variable changes affect outcomes
Determine the most favorable business strategy
Evaluate best- and worst-case scenarios in real-time
What-if analysis supports scenario modeling without modifying the underlying data model or requiring technical scripting skills.
R Environment Setup
Intellicus supports integration with R for advanced data science workflows. You must install the following R libraries on your R server:
lintrrandomForestdplyrRserve
Install any additional libraries required by your custom R scripts or algorithms.
User Roles and Access
Role | Capabilities |
|---|---|
Super Administrator | Create engine and file source connections |
Designers / Data Scientists | Write R scripts, add data science steps, and transform data |
End Users | Run reports with predictive insights and use what-if analysis for decisions |
Note
R scripts can be authored and managed directly within Intellicus.
In the following sections, we will cover:
Creating connections to data science engines
Adding and configuring the Data Science Engine step at Query Object level
Running reports and using predictive insights with what-if modeling
Read more:
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