Understanding ETL vs. ELT in Power BI || Belayet Hossain

When working with data in Power BI, it's essential to grasp the concepts of ?????? (??????????????, ??????????????????, ????????) and ?????? (??????????????, ????????, ??????????????????). These are two different approaches to data processing and integration that prepare data for analysis and visualization. Here's a comprehensive overview tailored for newcomers to Power BI.

????. ???????? ?????? ?????? ?????? ???????

?????? (??????????????, ??????????????????, ????????):

• Extract: Pulling data from various source systems (databases, files, APIs, etc.).
• Transform: Cleaning, shaping, and converting the extracted data into a suitable format for analysis.
• Load: Importing the transformed data into the target system (like Power BI’s data model).

?????? (??????????????, ????????, ??????????????????):

• Extract: Pulling data from source systems.
• Load: Loading the raw data directly into the target system.
• Transform: Performing data transformations within the target system itself.

?? ??. ?????? ???? ?????? ?????? ?????? ?????????? ???? ?????????? ?????

?? ??. ?????? ???? ?????????? ????:

A. ??????????????: Use Power BI’s Get Data feature to connect to various data sources (e.g., Excel, SQL Server, web services).

B. ??????????????????:

• Power Query Editor is where transformations occur.
• Common transformations include:
• Filtering Rows: Removing irrelevant data.
• Removing Columns: Dropping unnecessary fields.
• Changing Data Types: Ensuring data is in the correct format.
• Merging Queries: Combining data from multiple sources.
• Creating Calculated Columns: Adding new data based on existing fields.

C. ????????: After transformations, the cleaned and structured data is loaded into Power BI’s data model for visualization and analysis.

???????????????????? ???? ?????? ???? ?????????? ????:

• ???????? ??????????????: Ensures data is clean and consistent before loading.
• ??????????????????????: Reduces the amount of data processed during analysis by handling transformations upfront.
• ??????????????????????: Transformation steps are documented and can be reused or modified easily.

?? ??. ?????? ???? ?????????? ????:

While Power BI emphasizes ETL via Power Query, ELT can be relevant in certain scenarios, especially when leveraging powerful data sources that can handle transformations efficiently.

A. ??????????????: Connect to the data source and extract raw data without significant preprocessing.

B. ????????: Load the raw data directly into the target system (e.g., a cloud data warehouse like Azure SQL Data Warehouse).

C. ??????????????????:

• Perform data transformations within the target system using its processing capabilities (e.g., SQL queries, stored procedures).
• Power BI then connects to this already-transformed data for reporting.

???????????????????? ???? ?????? ???? ?????????? ????:

• ??????????????????????: Offloads heavy processing to powerful data sources.
• Flexibility: Allows transformations to be tailored within the data source environment.
• ????????????????????: Beneficial when dealing with large datasets that are better processed within the data warehouse.

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?? ??. ???????? ???? ?????? ?????? ????. ?????? ???? ?????????? ????

?? ?????? ?????? ????????:

• ???????? ?????????????????????????????? ?????? ????????????????????: When the required data cleaning and shaping can be efficiently handled within Power BI.
• ???????????????????? ???? ??????????????????: For straightforward data workflows without the need for extensive backend processing.
• ?????????? ??????????????????????: When quickly prototyping reports and dashboards without altering the underlying data sources.

?? ?????? ?????? ????????:

• ???????????????? ?????????? ????????????????: When working with massive volumes of data that benefit from the processing power of dedicated data sources.
• ?????????????? ??????????????????????????????: When transformations are too complex or resource-intensive for Power BI to handle efficiently.
• ?????????????????????? ???????? ????????????????????: When multiple reports or applications need to access the same transformed data, ensuring consistency across platforms.

?? ??. ?????????????????? ???????????????? ???? ?????????? ????

?? ?????????????? ??: ?????????? ?????? ???????? ?????????? ??????????

????????????????: You have sales data in multiple Excel files and need to consolidate, clean, and analyze it in Power BI.

??????????:

1. ??????????????: Use Get Data to import the Excel files into Power BI.
2. ??????????????????:

• Remove unnecessary columns (e.g., metadata or blank columns).
• Filter out irrelevant rows (e.g., sales from previous years).
• Merge data from different files into a single table.
• Create calculated columns (e.g., Total Sales = Quantity × Price).

3. ????????: Load the transformed data into the Power BI data model.

4. ??????????????: Build visualizations and reports based on the cleaned data.

?? ?????????????? ??: ?????????? ?????? ???????? ?? ???????? ??????????????????

????????????????: Your organization uses Azure SQL Data Warehouse to store large transactional data. You need to analyze this data in Power BI.

??????????:

1. ??????????????: Connect Power BI directly to Azure SQL Data Warehouse.
2. ????????: Load raw transactional data into the warehouse without significant preprocessing.
3. ??????????????????:

• Within Azure SQL Data Warehouse, create SQL scripts or views to:
• Aggregate sales data by region and product.
• Calculate key metrics (e.g., year-over-year growth).
• Clean and standardize data formats.

4. Connect Power BI:

• Use ?????? ???????? to connect to the transformed views or tables in Azure SQL Data Warehouse.

5. ??????????????:Create reports and dashboards using the already-transformed and aggregated data.

?? ??. ???????? ?????? ?????????????????? ?????????????? ???????? ?????? ?????? ?????? ???? ?????????? ????

• ?????????? ???????? ??????: As a beginner, focus on learning Power Query within Power BI to handle most data transformation needs. It's user-friendly and powerful enough for many scenarios.
• ???????????????????? ???????? ???????? ??????????????: Know the capabilities of your data sources. If you're using a robust data warehouse, explore how ELT might benefit your workflows.
• ???????????????? ??????????????????: Power BI Dataflows allow you to create reusable ETL processes that can be shared across multiple reports and dashboards. This promotes consistency and efficiency.
• ???????????????? ??????????????????????:

> For ETL: Apply transformations that reduce data volume early in the Power Query process to enhance performance.

> For ELT: Utilize the data source's processing power by pushing down as many transformations as possible.

• ?????????????????????????? ?????? ??????????????????????:

> ETL: Keep track of transformation steps within Power Query to ensure they are well-documented and maintainable.

> ELT: Document transformations performed within the data source to facilitate collaboration and troubleshooting.

• ???????? ??????????????????: Use descriptive names for queries, steps, and transformations within Power Query to maintain clarity.

?? ??. ????????????????????

Both E???? and ?????? are valuable approaches in the context of Power BI, each with its own advantages depending on the specific use case. As a beginner:

• ???????????? ?????????? ?????????? (??????): It will cover most of your data transformation needs within Power BI and provide a solid foundation for data manipulation and analysis.
• ?????????????? ?????? ???????? ??????????????????????: As you become more comfortable and work with larger or more complex datasets, consider leveraging ELT by utilizing the processing capabilities of your data sources.