While the principles of Agile have entered most of the IT application projects, the world of Business Intelligence is one where large legacy BI projects in tools like IBM Cognos, Oracle, SAP Business Objects, Microsoft BI stack and more have persisted. According to Gartner this is called Mode 1 IT and the outcome of it is everlasting projects controlled by IT.

The growth of visual discovery tools like Qlik and Tableu has exposed data analysis capabilities to a larger audience, thus expanding the number of “information producers” inside an organization, while Cloud BI platforms now represent a viable alternative to the legacy BI platforms as previously addressed. Key drivers to this are innovation in areas of IOT, Customer Experience and Automation.

The new way of building modern and Smart Analytic solution refers to the use of Agile software development, preferable Cloud for BI projects to reduce the time it takes for traditional BI to show value to the organization, and to help in quickly adapting to changing business needs. Agile BI enables the BI team and managers to make better business decisions, and to start doing this more quickly.

We think that if you take a look at your analytics team, the following findings are quite common. This has a large affect to the business.

1. Instead of finding data users create duplicates of data -> takes time -> create governance challengesUsers cannot find the right dataExposes a business- & glossary layer
2. Users collect data without governance -> decisions can be based on incorrect dataData exist only in sourcesExposes data in a Data Lake and provides a governed view of mode 3 data
3. Users create their own data lakesTake long time for IT to deliver data i.e lack of governed data-self service for usersAllows mode 3 data but with governance, offer Self Service Data Prep
4. Multiple versions on the truth, Inefficient process using excel, person dependent in regards to insight, analysis, business rules and maintenanceBusiness critical data and calculations are executed and stored in excelHolds a logical view of all data and business rules which enables reuse of data assets
5. Users cannot trust data, decisions based on wrong calculations, lack of data lineageBusiness rules are hidden in code in different places without insight of business rules conflictsHolds a logical view of all data and business rules which enables reuse of data assets
6. IT can solve 1 & 2 BUT 3 will always exist and needs to be handled in a way for IT to maintain governance and business flexibilityIT does not support multiple modes

  1. IT delivered data from DW or Cubes
  2. IT delivered data from Data Lake

c. Users collect and stores own data

Allows finding 1, 2 & 3 but with governance and offering Self Service Data prep


The power of a new solution helps with:

  • Data Governance: support Super Users with data definitions, customized objects, calculations but also self-service data blending
  • Federated view of dimensional data to minimize duplication of data, can also be combined with federation of sources together with a Live Access to where the data live
  • Data Blending – Blend individual data with centralized master data, without data movement or replication, and while maintaining enterprise security policies.
  • Support standard users with simplified view of datasets i.e. several Custom Subject Areas
  • Support advanced customization such as:
    • Drill paths and maps
    • Custom variables
    • Custom attributes/dimensions
    • Custom measures such as Calculated or Bucketed Measures
    • Creating aggregates
    • Keep track of usage
    • SSO

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