World around us is filled with data and everything we do generates data and also every decision we make is based on meaningful information derived from data. Our business process mostly involves enterprise systems and their external interaction points. But to get meaningful information from these it’s often required to combine & analyze the data that is internally generated from various organizations within the enterprise as well as externally generated outside of our business.
Think “Data First” to drive business value
Data cleansing deals with detecting and removing errors and inconsistencies from data in order to improve the quality of data. Data quality problems are present in single data collections, such as files and databases, e.g., due to misspellings during data entry, missing information or other invalid data. When multiple data sources need to be integrated, e.g., in data warehouses.
federated database systems or global web-based information systems, the need for data cleaning increases significantly. This is because the sources often contain redundant data in different representations. In order to provide access to accurate and consistent data, consolidation of different data representations and elimination of duplicate information become necessary.
The consolidation mechanism of the DC3 framework ensures that the data from various sources with various formats are consolidated into logical models which are creatable, configurable and extendable.