The need for data integration

 In modern banking technology environment , the quest to get hold of data is a very complex exercise. First the data about the transaction has to be collected and there are rules on what to collect , how to collect and from where you are receiving this data. Then the need to transform the data into a form that can be ingested ,indexed and visualized by the product developers. After this, the data has to be moved to analytical platforms to slice and dice the data in a way that will make sense to the business teams. Finally the data has to be stored for a period of time . While doing all this the data has to be secure and protected  from hacking or loss.

Data Integration is the discipline of IT that comprises of the practices. architecture and tools that allows the bank to manage their disparate data sets in a coherent manner. This discipline covers all flavors and  types- data ingestion, data transformations, data processing, data pipelines, data synchronization, data virtualization, data fabrics, data engineering, data staging, streams data and data services to name a few.

In absence or lack of process around your data it can quickly overwhelm banking operations and lead to deterioration of services and impact the bottom-line.

Luckily this is a well known problem for which many approaches  and technical solutions are available. The challenge is all these solutions cover some parts of the puzzle and the bank has to figure out what works best for them. Understanding your data lifecycle, who needs access to what data are the key aspects to figure--how to do once a path has been decided is the easier part.