What are the Transformations available in SSIS?
Aggregate: It applies aggregate functions to Record Sets to produce new output records from aggregated values.
Audit: Adds Package and Task level Metadata – such as Machine Name, Execution Instance, Package Name, Package ID, etc..
Charactermap: Performs SQL Server column level string operations such as changing data from lower case to upper case.
Conditionalsplit: Separates available input into separate output pipelines based on Boolean Expressions configured for each output.
Copy column: Add a copy of column to the output we can later transform the copy keeping the original for auditing.
Dataconversion: Converts columns data types from one to another type. It stands for Explicit Column Conversion.
Dataminingquery: Used to perform data mining query against analysis services and manage Predictions Graphs and Controls.
Derivedcolumn: Create a new (computed) column from given expressions.
Exportcolumn: Used to export a Image specific column from the database to a flat file.
Fuzzygrouping: Used for data cleansing by finding rows that are likely duplicates.
Fuzzylookup: Used for Pattern Matching and Ranking based on fuzzy logic.
Importcolumn: Reads image specific column from database onto a flat file.
Lookup: Performs the lookup (searching) of a given reference object set against a data source. It is used for exact matches only.
Merge: Merges two sorted data sets into a single data set into a single data flow.
Mergejoin: Merges two data sets into a single dataset using a join junction.
Multicast: Sends a copy of supplied Data Source onto multiple Destinations.
Rowcount: Stores the resulting row count from the data flow / transformation into a variable.
Rowsampling: Captures sample data by using a row count of the total rows in dataflow specified by rows or percentage.
Unionall: Merge multiple data sets into a single dataset.
Pivot:Used for Normalization of data sources to reduce analomolies by converting rows into columns
Unpivot: Used for denormalizing the data structure by converts columns into rows incase of building Data Warehouses.