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.
