Power BI Data Integration: A Practical Approach to Working with Multiple Data Sources

Introduction In modern analytics ecosystems, data is distributed across heterogeneous sources, including relational databases, flat files, APIs, and cloud-based platforms. For data analysts and BI engineers, the primary challenge lies in designing a robust data ingestion layer that can efficiently connect, extract, and standardize data from these disparate systems. Power BI addresses this challenge through its extensible data connectivity framework and the Power Query (M) engine, which enables seamless interaction with both structured and semi-structured data sources. However, establishing connections is only the initial step. The real complexity lies in handling schema inconsistencies, managing data types, resolving missing or duplicate records, and transforming raw data into a normalized format suitable for analytical modeling. This guide explores the technical process of integrating multiple data sources into Power BI, focusing on connection mechanisms, query folding where applicabl