Types of Dataset Refresh in Power BI || Belayet Hossain

A ?????????????? ?????????????? in Power BI updates the dataset with the latest data from your source (???????? ???? ?????????? ????????, ?????? ????????????????, ???? ???????????? ??????????????) to keep your reports and dashboards current.

Power BI offers several ways to refresh datasets, depending on how often the data changes and the size of the dataset.

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→ ????????????????????: A manual refresh triggered by the user when they want to update the dataset.

→ ?????? ????????: Useful for data that doesn’t need frequent updating, allowing you to control when it’s refreshed.

→ ???????? ??????????????: Excel files, SQL Server, CSV files, cloud-based data like Azure SQL Database.

→ ??????????????: Let’s say you’re tracking sales data in an Excel file on OneDrive. After updating October’s sales figures in the Excel file, you log into Power BI and manually trigger an On-Demand Refresh to pull in the latest data.

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→ ????????????????????:A scheduled refresh that automatically updates the dataset at specific times.

→ ?????? ????????: Ideal for regular updates, like daily or weekly reports, without needing manual refreshes each time.

→ ???????? ??????????????: SQL Server, Azure SQL Database, Oracle, Excel files on OneDrive/SharePoint, and other cloud services.

→ ??????????????: You’re creating a dashboard that shows your company’s website traffic. Setting a scheduled refresh at 6 a.m. every day ensures that your team sees the latest data every morning without needing to refresh manually.

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→ ????????????????????: A targeted refresh that updates only new or recent data, leaving historical data untouched. This is faster and more efficient for large datasets.

→ ?????? ????????: Useful for large datasets where only the most recent data needs frequent updates, such as ongoing sales or transaction data.

→ ???????? ??????????????: SQL Server, Azure SQL Database, Oracle, and data sources that support Query Folding (the ability to push queries back to the data source).

→ ??????????????: You have a large sales history table with millions of records spanning multiple years. Instead of refreshing the entire dataset, Incremental Refresh only updates the last month’s data, keeping the other years untouched. This greatly reduces refresh time and keeps reports updated efficiently.

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→ ????????????????????:These modes don’t import data into Power BI but instead query the data source each time a report or dashboard is accessed.

→ ?????? ????????: Best for real-time dashboards or cases where data changes rapidly, like inventory levels or stock prices.

→ ???????? ??????????????: SQL Server, Azure SQL Database, Oracle, SAP HANA, and other sources that support DirectQuery or Live Connection.

→ ??????????????: You’re creating an inventory dashboard for a warehouse. By using DirectQuery mode, every time a user opens the dashboard, it fetches the latest stock levels directly from the warehouse’s SQL Server database, showing real-time data without needing manual refreshes.

??. ???????????? ?????????????? (?????????????????? ????????????):

→ ????????????????????: Combines Import and DirectQuery within a single model, allowing some data to be imported and other data to be live queried.

→ ?????? ????????: Ideal for mixed-use cases where historical data is rarely updated, but current data needs to be live or frequently refreshed.

→ ???????? ??????????????: SQL Server, Azure SQL Database, and other sources compatible with DirectQuery.

→ ??????????????: You’re building a report that combines last year’s historical sales (imported data) with current month’s sales (DirectQuery). The historical data is loaded once and only refreshed monthly, while the current month’s sales are live, pulling updates as needed.

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

→ ????-???????????? ?????? ?????????????????? ??????????????: Basic options that refresh all data at once, suitable for smaller datasets.

→ ?????????????????????? ??????????????: Updates only new data, ideal for large datasets with historical data.

→ ??????????????????????/???????? ????????????????????: Enables real-time data but depends on the source’s responsiveness.

→ ???????????? ??????????????: Offers flexibility by combining real-time and historical data in a single report.

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