Thinking DV is not for you?

if you’ve ever wondered about data vault modeling, then wonder no more.  now is the time for all good people to come to the table and at least see what it’s about.  it’s free, it’s open-source architecture (if you can call it that), and it’s been proven successful in many environments.  the recent of which logica unveiled in presentations in the netherlands, germany, and france.  i too have a couple of success stories up my sleave that i’d like to share with you.  this entry takes a candid look at some of this grand information and the success that is coming from using the data vault modeling, and methodology.


(logica and logica bi framework, with data vault at the heart)  the first success is a global team effort put together by logica, for a customer in sweeden called tele2.  here are some of the statistics that were presented (in case you missed the presentation):

** note: the source of this information is aytekin keskin of logica.

sources: logical 44,  physical > 130

  • access control system
  • billing system
  • call center
  • campaign management tool
  • content billing gateway
  • cdr systems
  • crm systems
  • device detection system
  • partners and competing operators
  • data of organisation
  • demographic data on individuals
  • finance
  • sales
  • site catalogue
  • network system
  • support for planning and network implementation
  • interconnection with others networks
  • broadband management
  • order handling system
  • porting handler
  • unsubscription
  • product management
targets: 10 subject areas
  • customer base management
  • financial management
  • sales channel management
  • service delivery management
  • supply chain management
  • billing management
  • customer campaign management
  • customer operational management
  • product lifecycle management
  • cdr operational store
 the team!!   locations: 14 countries 8 time zones (give or take a few)
  • sweden
  • norway
  • russia
  • germany
  • austria
  • baltics
  • croatia
over 3000 business requirements and over 300 tb estimated data volume
requirements they worked through using the data vault modeling and methodology:
  • design and implement a global bi/dw solution
    • supporting country business functions
    • supporting tele2 corporate functions
  • improve bi & dwh practice within tele2
    • less costly and faster processes
    • a enterprise-wide dwh based on common definitions
    • higher information quality and more usage
    • improved technical solution
    • ensure adaptability & flexibility
    • ensure high-performance
  • replace existing dwh platforms
    • migrating historical data
    • migrating existing reporting and analytics

the data vault proved for them to be the only way to meet all these requirements, and to solve the problems that tele2 faced.  tele2 is still an on-going project, but is bound to be successful going forward.


 yet another huge company that logica has worked on, and provided a data vault to solve their business problems…  the source for this information is: liesbeth hozee, also working for logica

managing director herman bennema:

“this database is vital to vektis. the data is needed for the risk equalization between health insurance companies. it forms the basis of our information products, that support the daily activities of our customers and which they employ for strategic decision and policy making”
“the datawarehouse is vital to vektis, striving to be a reliable source of high quality information”

organizational challenges:
  • enabeling the organisation to take over maintenance
  • working within fixed deadlines in a learning organisation
  • convince dataminers that editing of data by hand destroys trace ability
  • selecting the right business rules
  • scaling and upgrading of infrastructure in pace with project needs 
  • high visibility due to impact on society
how does the data vault help?
  • dv modeling technique improves flexibility and scale ability 
  • implementing programmed business rules (business vault) secure trace ability and transparancy and help to minimise data handling
  • results of quality rules in a separate datamart support dialogue on data quality with data delivering parties
  • methodology with strict building standards ensure resilience

i have a number of other customers, and as time moves on, i will share similar success stories.  i feel it’s as important to share the successes and highlight the companies that have done so, as it is to discuss the issues and best practices (as i often do in the blog).

remember, in the coaching area, you can learn how to implement solutions like this, how to take control of your enterprise projects, and how to be a success with the data vault.

do you have a success story for your company that you’d like to share?  send it to me!

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