Data Preparation and Secure Connection Strategies for LLM Integration in Power BI

Strategies for Data Preparation and Secure Connection in Power BI for LLM Integration
30 hp – Power BI and LLM integration

Introduction
This thesis explores strategies for ensuring the data used in Power BI is well-prepared and securely connected for interaction with LLMs. The focus is on data cleaning, transformation, and establishing a secure connection between Power BI and LLMs for safe and efficient analysis.

Background
Effective LLM integration with Power BI requires well-structured data and secure connections to protect sensitive information. This is particularly important when dealing with vehicle performance data, where data integrity and security are critical. Challenges in data preparation and secure connection need to be addressed to ensure successful integration.

Objective
To develop strategies for data preparation, transformation, and secure connection protocols for integrating LLMs into Power BI, ensuring that both data integrity and security are maintained during analysis.

Job description

• Investigate data preparation techniques for LLM integration.
• Design secure connection strategies between Power BI and LLMs.
• Implement and test data preparation methods and secure connections in a real-world scenario.
• Ensure compliance with data security and privacy regulations.

Education/program/focus
Master’s in Cybersecurity, Data Science, AI, or related fields with a focus on data security, data preparation, and business intelligence tools.
Having knowledge of vehicle performance is a bonus.

Number of students: 1
Start date for the thesis work: 2025-02-03
Estimated duration: 22 weeks, until 2025-07-04.
In average min. 2 office-days per week.
Language of work: English, Swedish.
Location of work: Södertälje and Stockholm, Sweden.

Students from outside Greater Stockholm can rent a subsidized Scania apartment in Södertälje.

Payment before taxes: 20'000 SEK at the start, 20'000 SEK after the final report was approved.

Contact persons and supervisors
Mohammad Davari, Data Analyst, Vehicle Validation, mohammad.davari@scania.com
Mattias Borg, Group manager, Vehicle Validation, mattias.borg@scania.com

Application:
Please enclose personal letter, CV and the list of grades from the latest M.Sc. studies.

An academic reference is required.

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.