Data Warehouses

Many organizations have difficulty in creating value out of their computerized and archived data. This has many reasons:

    • Data is stored in disparate operational systems, whereby it is difficult to achieve good quality in databases, and data cannot be compared due to different metadata structures and coding standards.
    • Data is stored in old technological platforms whereby it is difficult to retrieve and analyze it.
    • Data in operational systems is too big, and these systems are optimized for transaction processing. Analysis requiring big volumes of data is difficult to perform, and such an activity degrades system performance and responsiveness drastically.
    • It is not possible to keep historical data in operational databases since big size is enemy of performance, and old data gets deleted. However, access to historical information is critical to identify business profitability and customer trends. Identifying discontinuities (lost customers, product model changes etc) is not possible without historical data.
    • Even if data is easy to retrieve out of databases, users of data want to have efficient analysis tools, and want to be independent of IT professionals.

Creation of a data warehouse, and creation of (departmental) data marts from the data warehouses, if necessary, is very crucial for an organization in order to create value from its data. This is also a first step towards more effective management and strategic information systems like balanced scorecards, and towards identification of business and customer value and trends which are crucial to today’s CRM implementations.

We help our customers realize increased value from their operational databases by:

    • Designing their data warehouse by identifying their critical business transactions (facts), and identifying important attributes (dimensions) of these transactions. We help our customers identify their important dimension attributes (whether age is important for insurance premium setting, whether temperature is important for the selling (hence stock levels) of beverages at a supermarket etc.).
    • Advising our customers for performance/availability/scalability/redundancy during selection of required hardware and software, and managing the implementation of these equipment.
    • Creating complete software solutions to populate data warehouse initially, and to regularly feed it with new transactions from operational systems. Maintenance of summary fact tables (aggregates) is part of our solution.
    • Advising our customers during selection of On-line Analytical Processing (OLAP) tools and other reporting tools, in order for them to get the best benefit from their data warehouse investments.
    • Designing operational aspects of our customers’ data warehouse shops, creating procedures and standards that are necessary to run a data warehouse, and training our customers’ staff.
    • Taking over the control of our customers’ data warehousing operations based on SLAs, if requested.