Bigdata Homogenisation module,integrated with MUNTHAN™ include following products: -
Bring Disparate Data Sources Closer. Make them Talk to each other. Generate Innovative Views.
In today's competitive world, organization need to be competitive and be in control regarding its decision making processes. Legacy data is
urgently required for making such decisions particularly when data has to be analyzed and viewed for past trends and facts.
As a matter of fact, old data resides in disparate systems in terms different database systems, files, different operating systems, file-folders
in the form of excel files, image files, documents in different formats etc.
In such cases, there exists an urgent need for an efficient system that brings on the table all old/legacy information systems, unstructured data, and presents an information view that makes the organization capable of correlating & analyzing all information at one place. Looking at the need, Tesarrow integrates an efficient Data Homogenization System that cater to above mentioned requirements.
Flexible User Interface for Analysis & Comparative Study
Flexible Control Flow for data Extraction & Induction
Application Program Interface
Other Features Include:
Configure Unwanted Data Packets. Remove before they Consume Resources. Make the System Learn.
Data cleansing, normalizing and securing are the most important and vital aspects in the process of data mining, warehousing and
advanced analytics. Apart from the processing of large volume, heterogeneous, velocity and complexity of data, the data harmony is equally important for
further processing. All involved components need to work in conjunction with each other to make up to the scenario where user is able to view
structured analysis reports.
Unwanted, undesired or extra fields in the diversified & complex source data may create great deal of deviation in the final report views; and therefore in this respect, we can categorize such extra fields as garbage. Tesarrow integrates an advanced view modeling structure in the Bigdata platform that facilitates raw views of data fields. The analyst would be able to filter mark all undesired fields and the system processes as required. For further processing of similar data fields, the machine learns and prompts user for correcting actions needed, if any.