Working with Data Sources in Tableau for MCA Semester 3 or IT Students

 Prepared By : Prof. Uday Shah (HOD-IT)

Working with Data Sources in Tableau

1. Tableau – Connect to a Data Source

• Tableau allows you to connect to multiple data sources like Excel, CSV, SQL Server, Google Sheets, etc.

• From the Start Page, click on Connect in the left sidebar.

• Select the type of data you want to connect (e.g., Excel, Text, Server).

• Once selected, browse your file location or enter server credentials.

• Tableau loads the data into the Data Source Tab.

• You can preview data in a grid-like format before importing it.

• You can rename fields directly here for clarity.

• Multiple tables from the same file can be loaded.

• Drag tables into the canvas to define relationships.

• Data can be Live Connected or Extracted for performance improvement.

• Live Connection keeps data updated from source.

• Extract stores a snapshot for faster processing.

2. Connect with Text File

• Used to connect .txt or .csv files.

• In Tableau, click Connect → Text File.

• Select your CSV or TXT file.

• Tableau automatically detects delimiters (comma, tab, pipe).

• You can change delimiter type in connection settings.

• Supports UTF-8 encoding.

• Header rows can be detected automatically.

• Data preview is shown in the Data Source window.

• Column names and data types are inferred but editable.

• Very useful for importing large exported reports.

• Can be combined with joins if other sources are connected.

• Data Extracts can speed up processing for large text files.

3. Connect with Excel

• Most common data connection type in Tableau.

• Supports .xls and .xlsx formats.

• Go to Connect → Microsoft Excel.

• Select the file from your computer.

• All sheets are displayed on the left.

• Drag sheets into the canvas to load them.

• Multiple sheets can be joined/related.

• Data can be pivoted within Tableau.

• Field names and data types are inferred automatically.

• Can connect with named ranges in Excel.

• Large Excel files might need extracts for speed.

• You can refresh Excel data without re-importing.

4. Tableau Extracting Data

• Extracting creates a static snapshot of your data.

• Improves performance with large datasets.

• File is stored as .hyper format in Tableau.

• Supports filters to limit extracted data.

• Extracts can be refreshed manually or scheduled (Tableau Server).

• Allows offline analysis without original data connection.

• Reduces load time for dashboards.

• Enables better aggregation performance.

• Extracted data can still be filtered in Tableau.

• Can be optimized for faster query execution.

• Extracts can be published and shared.

5. Data Connecting in Tableau

• Tableau supports Live and Extract connections.

• Live connection always fetches the latest data from the source.

• Extract connection stores a cached version.

• You can connect to multiple data sources simultaneously.

• Tableau allows blending/joining between different sources.

• Connection type affects performance.

• You can switch between Live and Extract anytime.

• Live is better for real-time dashboards.

• Extract is better for speed and offline use.

• Secure connections can be set up for databases.

• Data refresh schedules are available in Tableau Server/Online.

6. Tableau Editing Metadata

• Metadata includes field names, data types, and descriptions.

• You can rename fields for better readability.

• Change data types (String, Date, Number).

• Hide unnecessary fields.

• Create calculated fields.

• Change default aggregation (SUM, AVG, COUNT).

• Set geographic roles for location-based fields.

• Add comments for future reference.

• Group fields into folders.

• Metadata changes don’t affect the original source.

• Can be reset to original source state.

7. Tableau Data Joining

• Joins combine tables within the same data source.

• Supports Inner, Left, Right, Full Outer joins.

• Join keys define how tables match.

• Can join multiple tables together.

• Joins happen at row level.

• Useful when tables share common fields.

• Join performance depends on data size.

• Data preview shows join results instantly.

• Multiple join clauses are possible.

• Avoid unnecessary joins to improve speed.

8. Tableau Data Blending

• Combines data from different data sources.

• Requires a primary and secondary data source.

• Linking is done on common fields.

• Primary source fields have blue check marks.

• Secondary source fields have orange check marks.

• Useful for combining different database types.

• Works at aggregated level (not row level like joins).

• Blending is slower than joining in same source.

• Blended fields can be used in same visualization.

• Limited by aggregation differences between sources.

9. Tableau Replacing Data Source

• Allows switching one data source with another.

• Used when data source location changes.

• Keeps existing visualizations intact.

• Both data sources must have matching field names/types.

• Avoids rebuilding dashboards from scratch.

• Useful for moving from development to production.

• Can replace Excel with SQL for performance.

• Tableau automatically maps matching fields.

• Non-matching fields need manual remapping.

• Old data source is removed after replacement.

:: Best of Luck ::