View
130
Download
4
Category
Tags:
Preview:
DESCRIPTION
Firestarter SSIS 06 data flow (old 20010 presentation)
Citation preview
Data FlowThe Data Flow Task
Encapsulates the data flow engineExists in the context of an overall control flowPerforms traditional ETL in addition to other extended scenariosIs fast and scalable
Data Flow ComponentsExtract data from SourcesLoad data into DestinationsModify data with Transformations
Service PathsConnect data flow componentsCreate the pipeline
Data Flow TaskOne of the most valuable control flow tasks is the Data Flow Task.
Encapsulates the data flow engine
Load
Extract
Transform
Understanding a ETL Processing
Data Flow ElementsSQL Server Integration Services provides three different types of data flow components:
Data flow source - Sources extract data from data stores such as tables and views in relational databases, files, and Analysis Services databases. Data flow transformations - Transformations modify, summarize, and clean data.Data flow destination - Destinations load data into data stores or create in-memory datasets.
Integration Services PathsA 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.
Defining Data Flow SourcesIn 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
Understanding Data Flow Sources
OLEDB Oracle Connection
Data SourceSource Adapter
Data Flow DestinationsDestinations 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
Understanding Data Flow Destinations
ADO.NET Connection TargetDestination
Adapter
Defining Data Flow Transformations
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.
Understanding Data Flow Transformations
Mapping Columns and Dataflow Pipeline
DimProduct
ProductKey
Color
Name
Cost
DimProduct
ProductKey
Color
Name
Cost
DimProduct
ProductKey
Color
Name
Cost
Source
Transformation
Destination
Best Practices
Transformations
We can logically group them by functionality: Row Transformations Rowset Transformations Split and Join Transformations Auditing Transformations Business Intelligence Transformations Custom Transformations
Row Transformations 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
Rowset Transformations
Create new rowsets that can include
Aggregated values
Sorted values
Sample rowsets
Pivoted or unpivoted rowsets
Split and Join Transformations
Distribute rows to different outputs
Create copies of the transformation inputs
Join multiple inputs into one output
Perform lookup operations
Auditing Transformations Integration Services includes the following transformations to add audit information and count rows.
Business Intelligence Transformations
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.
ADO.NET Connection
Dataflow Summary
Sources
Transformations
Destinations
OLEDB Oracle Connection
EXCELConnection
DEMO
Recommended