Data Ware houses

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Data Ware houses

All successful businesses require concrete data warehouse design and architecture as a basic foundation. And every solid data warehouse requires a specifically designed, easy-to-maintain Extraction, Transformation, and Load (ETL) processes. Providing our deeper knowledge of Ralph Kimball techniques we deploy hands-on expertise with industry-proven tested ETL tools to construct effective, high-performance, data warehousing plans.

Any data warehouse project can appear difficult at the beginning, but Dataforce will partner with you for your complete project, from start to end. Our expert consultants have been involved in varied data warehousing and business intelligence projects over the last few years.

Dataforce has vast experience in providing end to end extensive Data Warehousing solutions to customers. Depending on your company’s contemporary state of data mart architecture, development and strategy, our Data Warehouse team evaluate and choose the correct tools, implementing the best solutions, and ensure the availability of accurate and timely information.

A data warehouse effectively maintains a copy of information from the system of source transaction. This architectural complexity provides the opportunity to :

  • Enhance the data quality, by offering consistent descriptions and codes, and fixing harmful data.
  • Provide the company’s information in a consistent manner.
  • Offer a single common data model structure for all data of importance irrespective of the data’s source.
  • Modify the data so that it becomes advantageous to the business users.
  • Modify the data so that it delivers best query performance, even for complex analytic queries, without affecting the operational systems.
  • Include value to operational business applications, specially customer relationship management (CRM) systems.
  • Enable the decision support queries easier to write.
  • Accumulate data from multiple sources into a single database so that a single query engine can be utilized to present the data.
  • Solving the problem of database isolation level lock contention during transaction processing systems caused due to attempts to run bigger, long running, analysis queries in transaction processing databases.
  • Maintenance of the data history, even when the source transaction systems do not.
  • Integrating the data from more than one source systems, providing a central view across the business enterprise. This is valuable advantage particularly when the company or business organization has grown by merger.
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