SSIS Tutorials

Mastering Data Integration with SQL Server Integration Services

Working with Diverse Data Sources

This tutorial guides you through the process of integrating data from various sources into your SQL Server Integration Services (SSIS) packages. Understanding how to connect to and manipulate different data types is crucial for effective data warehousing and business intelligence.

Objective

By the end of this tutorial, you will be able to:

  • Configure and use different connection managers for various data sources.
  • Import data from flat files (CSV, TXT).
  • Connect to and query relational databases (SQL Server, Oracle, MySQL).
  • Access data from XML and Excel files.
  • Handle common data transformation tasks during import.

Prerequisites

  • SQL Server Data Tools (SSDT) installed.
  • Basic understanding of SSIS package development.
  • Access to sample data files (e.g., CSV, Excel) and databases.

1. Connecting to Flat Files (CSV/TXT)

Flat files are a common source for data import. SSIS provides the Flat File Connection Manager for this purpose.

  1. In your SSIS project, right-click on the Connection Managers pane and select New Connection....
  2. Choose Flat File and click Add....
  3. Give your connection manager a descriptive name (e.g., CSV_Customers).
  4. Click Browse... to locate your CSV file.
  5. Configure the file format (e.g., Delimiter: Comma, Text qualifier: Double quote).
  6. Preview the data to ensure correct parsing.
Tip: For fixed-width files, select "Fixed width" in the Format dropdown and define column widths manually or automatically.

2. Connecting to Relational Databases

SSIS supports a wide range of relational database systems. The OLE DB Connection Manager is the most versatile for SQL Server, while ODBC or specific providers can be used for others.

2.1. SQL Server

  1. Right-click Connection Managers -> New Connection....
  2. Select OLEDB and click Add....
  3. Click New... to configure the connection properties.
  4. Enter the Server name and select the authentication method.
  5. Choose the Database name from the dropdown.
  6. Test the connection to verify.

2.2. Other Databases (Oracle, MySQL)

For databases other than SQL Server, you might need to install specific providers (e.g., Oracle Data Provider for .NET) and use the corresponding connection manager type (e.g., ADO.NET with the appropriate provider). The configuration process is similar, focusing on server details, credentials, and database names.

3. Connecting to Excel Files

Excel files can be accessed using the Excel Connection Manager.

  1. Add a new connection manager and select Excel.
  2. Specify the Excel file path.
  3. Choose the Excel version.
  4. The connection manager will treat sheets as tables.

4. Connecting to XML Files

For XML data, you can use the File Connection Manager and then specify an XML Source component in your Data Flow Task. Alternatively, if your XML is structured like a dataset, ADO.NET might be applicable.

5. Data Flow Task Configuration

Once connections are established, you'll use a Data Flow Task to move and transform data.

  1. Add a Data Flow Task to your Control Flow.
  2. Double-click the Data Flow Task to open the Data Flow tab.
  3. From the SSIS Toolbox, drag and drop a Source Component (e.g., Flat File Source, OLE DB Source, Excel Source).
  4. Configure the source component to use one of your created connection managers and select the specific table or file.
  5. Drag and drop a Destination Component (e.g., OLE DB Destination) to load the data into your target.
  6. Connect the source to the destination with a blue data path arrow.
  7. Double-click the destination component and configure it to use a destination connection manager and target table.

6. Data Transformations

Between the source and destination, you can insert Transformation components to clean, reshape, or enrich your data.

  • Derived Column: Create new columns based on expressions.
  • Data Conversion: Change data types.
  • Sort: Sort rows.
  • Aggregate: Perform aggregation operations.
  • Lookup: Join data with reference datasets.

For example, to convert a string column to a date:

Add a Data Conversion transformation.
Select the string column.
Choose the target data type (e.g., DT_DATE).
Give the new column an output alias.

Conclusion

Effectively integrating data from diverse sources is a cornerstone of data management. By mastering the use of different connection managers and understanding the capabilities of SSIS components, you can build robust and scalable data integration solutions.