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 Data Consolidation

The ETL team has followed the Inmon methodology of data consolidation across various data sources. The process of normalization helps the ETL team manage a large number of disparate data sources with ease and also helps at data cleansing. Also the maintainence is done with ease due to Inmon methodology. Data consolidation is a pre requisite for  Business Intelligence solutions from Turbodata.

The attached diagram indicates the approach used by the ETL team for data consolidation.



 Attached are the benefits associated with the ETL team's approach:


 The associated business benefits with the above approach are as follows:


The issues with  data consolidation could be numerous. Some of the issues are as follows:

·         Managing item masters: Once the data from multiple Tally data sources has been consolidated then the item masters could have duplicate item entries. Also there could be discrepancies in the manner in which the item names have been input. For example in one branch the item name could be say X and in another the same item could be named as X1. This results in complications when vouchers are to be consolidated. We could help consolidate Tally data.

·         Handling inserts, updates and deletes over large data loads: this could become complicated once large data loads are involved.

·         Issues with regards to inventory valuation, inventory ageing and accounts receivable and accounts payable ageing.


How do we solve the above problems:


·         Our process of data consolidation and  data transformation and data cleansing using normalization ensures that we do not have duplicates in item masters. We are also able to handle inserts, updates and deletes over large data loads effectively using the process of incremental loads. 

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