This week Dan Linstedt visited the Netherlands for a session about Datavault. The title of the seminar was about best practices in datavault. There were sessions about implementation about Tele2 and Vektis for showing how Logica implemented the datavault at some customers.
Below i bulleted the most significant subjects of the evening (to my viewpoint):
- There's 'no version of the truth' but a 'single version of the fact'. When you think about it, it makes sense to me. What he meant is that once there is a agreement about some KPI's and the system is implemented, some other managers, which didn't participate in the requirementsgroup, could have another viewpoint on a calculation of a KPI. Or perhaps a new manager want to measure KPI's in another way. Could be a point. But i see also some difficulties here:
- When the calculation of KPI changes to much, it's difficult to compare figures over a longer time. How do you handle this?
- I blogged about Self Service BI and i indicated that there will companywide KPI's but there will be also specific manager KPI's. How do you deal with this? Do you change the companywide KPI when a new manager enters the town? No, as in my former post said, you have to put a organisational unit in place: Governance committee. This group needs to decide about this stuff.
- Dan showed the following graph of a classic datawarehouse system. The problem with this kind of architecture that it's not auditable. The data is changed when the data enters the datawarehouse. I've done projects where the ETL developer got the blame because he didn't implemented the KPI in a proper manner. Who is the owner of the data? The business! Why should a ETL developer change the data? Hmm interesting viewpoint, but you could also say that the business didn't test the solution rightly. I know that testing is always a problem because of timeconstraints or less involvement of the business, etc.
- Dan showed another picture, as you can see below. In this picture the rules are propagated later in the architecture. This way the system is more auditable, you can change the KPI and recalculate it over you history. A next step is to implement a business vault in this model (not shown) which is a view over the datavault. This could be any datamodel that fits the business (e.g. Datavault modelling, starmodelling, etc).
- The physical model will be less important in the future. This point is not quite clear to me, yet. I think it has to do with cloudcomputing. You define a model and you don't care about the physical implementation of it.
- He also phrased in the same part that columnar MPP will be more important in the future. Agree with that.
- Data as a Service is growing and will take firm ground. Where the data is coming from will be less important. It could be that the master data will come from datasuppliers and that the datawarehouse in a company will be factgenerators. The dimensions are master data.
- Operational datawarehousing is also taking firm ground.
- Dan spoke also about dynamic datawarehouse. This can also be seen in the light of the agility developments. The datawarehouse will be more organic, it will change according to the developments in the business or communities. How? Good question. But i think that datavault is a organic like modelling technique and anchor modelling is even more flexible. This will enhance the dynamic datawarehousing!