Map CDC Transform in BODS

Using this transform’s input requirements (values for the Sequencing column and a Row operation column),  you can perform three functions: Continue reading “Map CDC Transform in BODS”

XML Pipeline in BODS

Processes large XML files of a nested structure in small instances.

With this transform, Data Services does not need to read the entire XML input into memory and Continue reading “XML Pipeline in BODS”

Hierarchy Flattening in BODS

This constructs a complete hierarchy from parent/child relationships, and produces a description of the hierarchy in vertically or horizontally flattened format. Continue reading “Hierarchy Flattening in BODS”

Data Quality Match Transformation in SAP BODS

Match transformation is used to identify the duplicates in the data based on the match criteria and a weighted score.

This transformation is used to determine the duplicates and consolidate them.

Using this transform we can- Continue reading “Data Quality Match Transformation in SAP BODS”

History Preserving Transform in BODS

This Transformation is used to preserve the history of the Data.

Suppose there is a customer, whose address is changed from NYK to LA. Then, after some time he moved to Texas. If the table is updated with new location or address, all the customer’s  past locations will be overwritten. There is a need to preserve the history of customer’s location to analyze the old data.

Using the History preserving transformation all the history data can be saved.

To apply the it, you need to have a table comparison done prior to this transformation- Continue reading “History Preserving Transform in BODS”

Data_Transfer Transform in BODS

This Transformation helps us in transferring the data in an effective mode.  Using this we can push the operands into the data base (like Group by or Order by on the database table).

Example: – Assume we are doing a lookup on the data and a group by on the same data in the same dataflow. If we are doing that on millions of records, it’s a performance hit. So if we use data transfer transformation, the data flow is split and runs as separate dataflows for lookup and also as separate dataflows for the group by/ orders by. Continue reading “Data_Transfer Transform in BODS”

Table Comparison in BODS

Table Comparison:

This is an important functionality in BODS. It compares two data sets and produces the difference between them as a data set with rows flagged as INSERT, UPDATE, or DELETE.

The Table_Comparison transform allows you to detect and forward changes that have occurred since the last time a target was updated.

 For those in BW, you can understand the importance of this transform if you have done full and delta loads to DSOs and Cubes.

Data Inputs

Continue reading “Table Comparison in BODS”

Key Generation in BODS

Key_Generation

To generate artificial keys in Data Integrator,  you can use either Key_Generation Transform or Key_Generation Function. It fetches max. existing key value from the table and uses it as a starting value. Based on this start key, transform/function increments the key value for each row. Continue reading “Key Generation in BODS”

Reverse Pivot in BODS

Reverse Pivot Transform in BODS:

This transform converts rows into columns. It will group the dataset of different rows into a single row with different columns. Observe the icon, it says that will convert rows to column. Continue reading “Reverse Pivot in BODS”