SSIS 2008 R2 data flow

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Firestarter SSIS 06 data flow (old 20010 presentation)

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SSIS 2008 R2 data flow

  1. 1. The Data Flow Task Encapsulates the data flow engine Exists in the context of an overall control flow Performs traditional ETL in addition to other extended scenarios Is fast and scalable Data Flow Components Extract data from Sources Load data into Destinations Modify data with Transformations Service Paths Connect data flow components Create the pipeline
  2. 2. Encapsulates the data flow engine Load Extract Transform
  3. 3. A Path connects two components in a data flow by connecting the output of one data flow component to the input of another component. A path has a source and a destination.
  4. 4. In SSIS, a source is the data flow component that extracts data from different external data sources and makes it available to the other components in the data flow. Sources have one regular output, and many sources in addition also have one error output. All the output columns are available as input columns to the next data flow component in the data flow. Sources extract data from: Relational tables and views Files Analysis Services databases
  5. 5. OLEDB Oracle Connection Data Source Source Adapter
  6. 6. Destinations are the data flow components that load the data from a data flow into different types of data sources or create an in-memory dataset. Destinations have one input and one error output. Destinations load data to: Relational tables and views Files Analysis Services databases and objects DataReaders and Recordsets Enterprise Edition only
  7. 7. ADO.NET Connection TargetDestination Adapter
  8. 8. SSIS Transformations are the components in the data flow of a package that give you the ability to modify and manipulate data in the data flow. A transformation performs an operation either on one row of data at a time or on several rows of data at once. For example aggregate, merge, distribute, and modify data and also can perform lookup operations and generate sample datasets.
  9. 9. DimProduct ProductKey Color Name Cost DimProduct ProductKey Color Name Cost DimProduct ProductKey Color Name Cost Source Transformation Destination
  10. 10. Best Practices
  11. 11. We can logically group them by functionality: Row Transformations Rowset Transformations Split and Join Transformations Auditing Transformations Business Intelligence Transformations Custom Transformations
  12. 12. The most common and easily configured transformations perform operations on rows without needing other rows from the source. These transformations, which logically work at the row level, often perform very well. Update column values or create new columns Transform each row in the pipeline input
  13. 13. Create new rowsets that can include Aggregated values Sorted values Sample rowsets Pivoted or unpivoted rowsets
  14. 14. Distribute rows to different outputs Create copies of the transformation inputs Join multiple inputs into one output Perform lookup operations
  15. 15. Integration Services includes the following transformations to add audit information and count rows.
  16. 16. cleaning data updating of a slowly changing dimension looks up values mining text running data mining prediction queries The final grouping of transformations lets you perform advanced operations on rows in the data flow pipeline.
  17. 17. ADO.NET Connection Sources Transformations Destinations OLEDB Oracle Connection EXCEL Connection

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