In Power BI, Extract, Transform, Load (ETL) refers to the process of extracting data from various sources, transforming it into a usable format, and loading it into the Power BI data model for analysis and visualization. Here’s a breakdown of each component:
· Extract (E):
o The “extract” phase involves retrieving data from multiple sources, such as databases, files, web services, or cloud platforms. Power BI supports a wide range of data sources, including Excel files, SQL databases, Azure services, Salesforce, Google Analytics, and many others.
o Users can connect to these data sources using Power BI Desktop or Power BI Service (cloud-based), and then extract the required data into Power BI for analysis.
· Transform (T):
o The “transform” phase involves cleaning, shaping, and transforming the extracted data to make it suitable for analysis. This includes tasks such as:
o Removing duplicates
o Renaming columns
o Formatting data types
o Handling missing or erroneous values
o Combining multiple data sources
o Calculating derived columns or measures
o Power BI provides a range of transformation options through its Power Query Editor, allowing users to perform data cleaning and manipulation tasks visually and intuitively.
· Load (L):
o The “load” phase involves loading the transformed data into the Power BI data model for visualization and analysis. Once the data has been extracted and transformed, it is loaded into Power BI datasets or dataflows.
o Power BI datasets are in-memory data models that store the cleaned and transformed data, along with any calculated columns or measures. Users can create reports and dashboards based on these datasets to visualize insights.
o Dataflows in Power BI Service offer a cloud-based data preparation option where users can build data transformation logic in Power Query Online and store the transformed data in Azure Data Lake Storage Gen2. This allows for data reuse and sharing across multiple Power BI datasets and reports.
Overall, the ETL process in Power BI enables users to extract data from various sources, transform it into a usable format, and load it into Power BI for analysis and visualization. This iterative process is foundational to creating meaningful insights and reports in Power BI.