In this article, we will explore the concept of data lineage in SQL Server and how it can be implemented using SSIS (SQL Server Integration Services). Data lineage is a crucial aspect of designing ETL (Extract, Transform, Load) workloads on a data warehouse. It helps track the source of a single record in the warehouse, which is essential for data governance and troubleshooting purposes.

Creating the Source Files

Before we dive into implementing data lineage, let’s start by creating two simple CSV files that will serve as our source data. For simplicity, we will use Microsoft Excel or Notepad to create these files. The first file, “Employee1.csv,” will have two columns: “Employee” and “Department.” The second file, “Employee2.csv,” will also have the same columns but with different data.

Designing the Database

Next, we need to design the database where we will load the data from the source files. For this demonstration, we will create a table called “Employees” with columns for “Employee,” “Department,” and “SourceSystemID.” The “SourceSystemID” column will store the information about the source file name from which the data has been populated.

Creating Connection Managers in the SSIS Package

With the source files and database design in place, we can now create the SSIS package to implement data lineage. We will start by creating the necessary connection managers. In SSIS, connection managers are used to establish connections to different data sources and destinations.

First, we will create a flat file connection manager for each of the source files. This connection manager will define the file path and format of the source files. We will also create an OLE DB connection manager for the SQL Server database where we will load the data.

Designing the Data Flow Task

Once the connection managers are set up, we can proceed to design the data flow task in the SSIS package. The data flow task is responsible for moving data from the source files to the destination database table.

In the data flow task, we will use a flat file source component to read data from each source file. We will then add a derived column transformation to add the name of the source file as the “SourceSystemID” in the database. Finally, we will use an OLE DB destination component to load the data into the “Employees” table.

Automatically Generating the Filename for Data Lineage

In the previous steps, we explicitly added the name of the source file as a derived column in the data flow task. However, this approach can be time-consuming if there are many sources in the pipeline. To simplify this process, we can use the “FileNameColumnName” property of the flat file source connection. This property automatically adds the path of the file as a new column, which can then be mapped to the destination column.

By utilizing this property, we can eliminate the need for a derived column transformation and streamline the data lineage implementation process.

Conclusion

Data lineage is a critical aspect of any ETL solution, and understanding how to implement it in SQL Server using SSIS is essential for data governance and troubleshooting purposes. By tracking the source of each record in the data warehouse, we can ensure data quality and maintain a stable and functional system.

In this article, we have explored the concepts of SQL Server data lineage and demonstrated how to implement it using SSIS. By following the steps outlined in this article, you can effectively track the source of your data and ensure the integrity of your ETL processes.