Does an enterprise need Data transformation Tools ? Answer is “Yes”. They are must for organization which are of enormous size and having many applications serving there different IT needs.
Data transformation Tools ( ETL ) tools are generally needed for enterprise’s “data consolidation” and “data integration” needs. It is very true that tools are not the only way to achieve needed objective. But they provide rapid project development and easy code maintenance.
Data warehouse is typical example of data consolidation, where you need to consolidate many systems to see overall performance of a business, product or service.
Enterprise applications integration is one of the potential ETL domains, Here tools enables you in such way that your applications can communicate to each other. In simple words “you can enable two applications to share data / status”.
Wondering why these kinds of scenarios persist. Here is a run down of few I am aware of.
Old school enterprises: were skeptical about IT solutions initially. Moreover budget was also a constraint and no good ERP was present. Vendors suggested different technologies for different types of software solutions. Justifying that "X" is good for finance and "Y" is good for operations management. This lead to multiple applications spreading across the enterprise.
Sometimes business model of enterprise also contributed to this situation, where individual business verticals were responsible for their IT infrastructure and because of this they ended up developing applications individually.
Fragmented data residing with many applications, Some of them having around (3000 to 5000 +) application which store and process important data of an enterprise.
Merger or acquisition: Does your company expand inorganically and acquire other companies. You need a simple way to club different applications. Say example you have an application which calculates sales personnel incentives for their quota. Here you can easily club new enterprise data by extracting it with Data transformation tools ( ETL ) and then by processing it with the same tool.
Enterprise data warehouse: Most of the tools are capable of reading different data formats from different sources to process them, for data warehouse they work as a data feeding system. This data is later used by reporting systems. Reporting systems provide different views of data in accordance to a user's need.
Forecasting application: You have a production unit and you want to forecast demand for the next quarter, so your vendor can supply the necessary stocks. Here ETL can pull data from different manufacturing units , stores, warehouses and after consolidation, it can give a rough picture about how much order needs to be placed for the next quarter.