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updated 5:09 AM CET, Nov 5, 2019
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Data Warehouse

  • Or how to successfully destroy every level of the data warehouse

    Dirk, I just read an article from you about Data Vault Modeling and the 13 tips for failure in the BI spectrum. A very interesting article with really good tips. Thanks a lot for that.Christian Ehrentraut, BI & Data Engineer

    Are you pampered with success and tired of the eternal pat on the back? You don't want to be so successful with your first attempt at implementing a Data Vault project that all your colleagues become jealous?

  • In recent weeks I have read so many pessimistic and negative articles and comments in the social media about the state of data modeling in companies in Germany, but also worldwide.

    Why? I don't know. I can't understand it.

    I know many companies that invest a lot of time in data modeling because they have understood the added value. I know many companies that initially rejected data modeling as a whole, but understood its benefits through convincing and training.

    Isn't it the case that we (consultants, managers, project managers, subject-matter experts, etc.) should have a positive influence on data modeling? To support our partners in projects in such a way that data modeling becomes a success? If we ourselves do not believe that data modeling is a success, then who does?

  • Im April 2013 war ich wieder beim Matter-Programm, Data Vault Architecture, in den Niederlanden wo ich Tom Breur kennen lernen durfte.

    In einer angeregten Diskussion über die Automatisierung von Data Warehousing mit Data Vault und der Eignung von Projektmethoden dafür lud Tom mich und Oliver Cramer zu einem Besuch von einem Kunden von sich ein: Der BinckBank.

    Tom Breur: “The best Agile BI shops I have ever seen.”

    Am 24. September 2013 war es dann soweit. Wir besuchten gemeinsam mit Tom die BinckBanck in Amsterdam und schauten uns das Agile Data Warehouse an, welches mit Data Vault aufgebaut wurde. Wir trafen uns mit dem BICC-Team, um über die Entstehungsgeschichte, die Umsetzung, die Herausforderungen und die Erfolgsfaktoren zu sprechen.

  • A few weeks ago I received a surprisingly open and honest feedback on my recently published article "13 tips...". I never ever expected that! After a short email exchange, I was allowed to publish the feedback anonymously. Below is the incredible feedback[3]. You see, you are not alone with the challenges of a Data Vault project:

    Hi Dirk

    Thanks for sending me the English version of the paper. I'm based in […] [1] and Data Vault is not generally established here yet.

  • All articles I wrote about data warehousing, Data Vault, data modeling and more.

    Enjoy reading and your comments are welcome.

  • If everything would happen at the same time, there would be no need to store historic data. We, the consumers of data, would know each and everything at the same instant. Beside all the other philosophical impacts, if time wouldn’t exists, is data still necessary?

    (Un)fortunately time exists and data architects, data modelers and developers have to deal with it in the world of information technology.

    In this category about temporal data I will collect all my blogposts about this fancy topic.

  • Immer wieder kommt in Projekten die Frage auf, besser gesagt die Diskussion, ob Constraints in der Datenbank physisch sinnvoll sind oder nicht. Meist gibt es Vorgaben von DBAs oder durchsetzungsstarken ETLern, die eine generelle Abneigung gegen Constraints zu haben scheinen, dass Constraints nicht erwünscht sind. OK, diese Woche wurde mir wieder das Gegenteil bewiesen. Doch wie heißt es so schön: Ausnahmen...

    Auf dem #WWDVC und im Advanced Data Vault 2.0 Boot Camp haben wir ebenfalls über dieses Phänomen gesprochen. Das scheint weltweit zu existieren. Dazu hat kurz nach dem #WWDVC auch Kent Graziano einen Blogpost verfasst. Auf LinkedIn gab es dazu einige Kommentare.

    Gut, wie argumentiert man am besten, bzw. was sind eigentlich die Vor- und Nachteile Constraints zu verwenden?

  • Objective review and data quality goals of data models

    Did you ever ask yourself which score your data model would achieve? Could you imagine  90%, 95% or even 100% across 10 categories of objective criteria?

    No?
    Yes?

    Either way, if you answered with “no” or “yes”, recommend using something to test the quality of your data model(s). For years there have been methods to test and ensure quality in software development, like ISTQB, IEEE, RUP, ITIL, COBIT and many more. In data warehouse projects I observed test methods testing everything: loading processes (ETL), data quality, organizational processes, security, …
    But data models? Never! But why?

  • OK, for those of you who just want to grab a promotion code... I'll make it short 😂:

    TEDAMOH

    As a speaker at both conferences I give you 15% on the DMZ EU and 20% on the DMZ US. You can register here.

    For those of you who are also interested in what I'm going to talk about, a few more informations:

  • DMZone2015Flyer

    Do you want to learn something about data modelling with Steve Hoberman? You want to explore new methods like Data Vault 2.0, Anchor Modeling, Data Design, DMBOK and many more? E.g. a keynote where Dan Linstedt, Lars Rönnbäck and Hans Hultgren talks together, and another one with Bill Inmon?

  • Wie bereits in meinem Blogpost Modellierung oder Business Rule beschrieben ist es notwendig sich bei der Datenmodellierung über Geschäftsobjekte, die Wertschöpfungskette, fachliche Details und die Methodik des Modellierens einige Gedanken zu machen.

    Oder doch nicht? Kann ich mit Data Vault einfach loslegen? Schließlich ist Data Vault auf den ersten Blick ganz einfach. Drei Objekte: HUBs, LINKs und SAT(elliten), einem einfachen Vorgehensmodell und ein paar wenige Regeln. Brauche ich für Data Vault noch die Datenmodellierung?

  • Read the full article, I wrote, in BI-Spektrum 05/2014.

    So long
    Dirk

    Data Vault im Einsatz beim Gutenberg Rechenzentrum

  • This year’s European Data Modeling Zone (DMZ) will take place at the wonderful German capital Berlin and I’m very happy to be again speaker at this great event! This year I’ll speak about how to start with a conceptual model, using a logical model and finally how to model the physical Data Vault. During this session we will do some exercises (no, no push-ups!!) to bring our brains up and running about modeling.

  • I am pleased to say that I will be participating at this year’s Enterprise Data & Business Intelligence and Analytics Conference Europe 18-22 November 2019, London. I will be speaking on the subject ‘From Conceptual to Physical Data Vault Data Model’ and (for sure) on my hobby horse subject temporal data: ‘Send Bi-Temporal Data from Ground to Vault to the Stars’. See my abstracts for the sessions below.

  • Months ago I talked to Stephan Volkmann, the student I mentor, about possibilities to write a seminar paper. One suggestion was to write about Information Modeling, namely FCO-IM, ORM2 and NIAM, siblings of the Fact-Orietented Modeling (FOM) family. In my opinion, FOM is the most powerful technique for building conceptual information models, as I wrote in a previous blogpost.

  • FCO-IM - Data Modeling by Example

    Do You want to visit a presentation about Fully Communication Oriented Information Modeling (FCO-IM) in Frankfurt?
    I’m very proud that we, the board of the TDWI Roundtable FFM, could win Marco Wobben to speak about FCO-IM. In my opinion, it’s one of the most powerful technique for building conceptual information models. And the best is, that such models can be automatically transformed into ERM, UML, Relational or Dimensional models and much more. So we can gain more wisdom in data modeling at all.

    But, what is information modeling? Information modeling is making a model of the language used to communicate about some specific domain of business in a more or less fixed way. This involved not only the words used but also typical phrases and patterns that combine these words into meaningful standard statements about the domain [3].