Data Warehouses

Do you have a lot of data in various systems? Do you want to use thousands of pieces of data for your business development instead of leaving it to sit unused? Your path from data to information starts right in the data warehouse. We will help you to build a data warehouse and teach you how to work with the data.

Why set up a data warehouse?

  • Data warehouse is an essential source of data for business applications and analyses. Its task is to create a base for the conversion of large amounts of data to commercial information.
    • Applications built over data warehouses are key business tools, for example CRM, reporting system, management information system, analytical and other systems.
      • A data warehouse can arrange information about millions of customer transactions. Nowadays it is a standard part of IT solutions for businesses and companies that work with large amounts of data operations in fields such as financial services, insurance, telecommunications, logistics, etc.

What is the purpose of data warehouse implementation?

  • Consolidation of data – processing data from various systems into a single database platform
    • Unification – identification and deduplication of clients, counterparts, contractors, etc. into a single master entity
      • Data integration – ensuring links between individual entities regardless of the source system and a unified viewing of data across various consolidated dimensions, unification of these dimensions and various code lists
        • Cleansing and checking of data – including reconciliations of financial and business data
          • Relieving operating systems – removing the burden associated with analytical tasks to another data repository

What we can do for you

  • Analysis – consolidated specification of user requirements, identified sources of data, technical analysis, solution architecture, hardware architecture, software to be used
    • Development – interface between the source and the warehouse, uploading transformed data into the stage layer, uploading transformed data into the warehouse core, including historisation, monitoring, management and administration of daily processing
      • Pre-implementation phase – preparation of testing scenarios, fixing errors, repairs, preparing handover documentation, training documentation, providing training staff, user and technical documentation, supporting pilot operation
        • Post-implementation phase – process monitoring, repairing errors in source data or transformations, including subsequent recovery process, administration of jobs in minor changes in processing, changes in processing during outages and scheduled system overhauls
          • Development of existing solution – expanding the transmitted data or adding new sources, changes on the part of the source data (modification or replacement of source systems), technological change in data warehouse solution (replacement or upgrade of technology), improving inadequate warehouse performance capacity (archiving old records, optimisation of processing or upgrading hardware)