In this ever-evolving world of technology, businesses need to remain competitive. That said, they must have robust business processes and 100% accurate data at any time. However, the irony is that most of the data that organizations receive from different sources is inconsistent and contains some errors.

As businesses aim to leverage data-driven decisions, access to accurate and correct data across the enterprise becomes essential. There may be many inconsistencies in the data – formatting issues, syntax errors, typos, irrelevant values, missing entries, etc. All of these have to be dealt with appropriately to obtain “clean” data. This leads us to the concept of data cleansing.

In this ever-evolving world of technology, businesses need to remain competitive. That said, they must have robust business processes and 100% accurate data at any time. However, the irony is that most of the data that organizations receive from different sources is inconsistent and contains some errors.

As businesses aim to leverage data-driven decisions, access to accurate and correct data across the enterprise becomes essential. There may be many inconsistencies in the data – formatting issues, syntax errors, typos, irrelevant values, missing entries, etc. All of these have to be dealt with appropriately to obtain “clean” data. This leads us to the concept of data cleansing.