Data Warehousing

Data Warehousing is more than simple hygiene.  Without proper Enterprise Data Warehousing, businesses are imposing an artificial ceiling on their ability to leverage their greatest asset – their data.

Data WarehousingWithout efficient access to data, for reporting purposes through business intelligence services, ensuring data quality for data analysis and financial reporting, or for preparation of data for direct marketing purposes, businesses reduce the effectiveness of their analytic and reporting projects and increase their development costs.

To discuss your requirements, and to identify a road map to your strategic data warehouse and data mining processes, please contact us.

Our consultancy road map for helping our clients unlock the value in their data is tested and proven,

  • Review of current data integration processes, data architecture, data warehousing ETL tools, and skill sets of available resources
  • Identify and implement tactical quick wins in these processes, improving efficiency and freeing up resources to support a strategic delivery
  • Gather requirements from all stakeholder groups, most likely
    • Finance & Exec
    • Marketing
    • Pricing and Commercial
  • Identify appropriate strategic data warehousing software and business intelligence tools
  • Develop data model to fit end user requirements
  • Develop data mining and ETL processes to populate data model

It sounds simple, but failing to gather requirements before beginning development, and starting to build data mining and ETL processes before having designed the data model will lead to a data warehouse design that quickly becomes out of date.

Data warehouses should,

  • Have its data warehousing technology supported by the business IT function
  • Have its ETL and Data Mining processes owned by the business, who should have the freedom to implement rapid change
  • Support a modular approach to end user tools, such as BI Software, Campaign Management Software, Analysis Software, so that best on class selection can take place and tools can be easily swapped
  • Support a modular approach to ETL and Data Mining Tools
  • Be integrated.  The web analytics data should join to the transactional database, and so on
  • Support the golden rule; the end user should never be more than 1 join or aggregation away from the data they need

The first step is to get an honest view from your data users, and we can help you to do that effectively, about whether they feel they could generate a lot more value if only they had efficient and reliable access to business data.

Contact us to discuss the route map for creating your enterprise data warehouse.

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