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Data Modeling

  • Auf dem 1. DDVUG Treffen hatten wir ein interessante Diskussion darüber, wo eigentlich die Datenmodellierung aufhört und Business Rules beginnen. Aufgehängt hatte sich dies an meiner Präsentation, in der es um einen Link ging, der eine 1:M (Hub A – (M) Link (1) – Hub B) Relation repräsentiert und über einen bi-temporalen Satelliten den gesteuert (end-dating) wird. So darf für jeden Eintrag im Hub B nur eine aktive Relation im Link existieren. Die Daten für das End-dating des Links kamen im von mir aufgeführten Beispiel bereits aus dem Quellsystem (Blogpost folgt bald).

  • 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.

  • Model driven decision making

    During #XP19 you’ll be able to take part in our (Matze and myself) deep dive session about Model driven decision making: Data (Vault) Modeling and Deep Learning. It has been designed to give you a (very) short hands-on and practical guidance.

    What is this 15 minute deep dive session about at #XP19?

  • 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?


    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?

  • After all, I am very happy to be a speaker at this year's Data Modeling Zone in Düsseldorf. Again, like at the Global Data Summit, I'm talking about one of my favorite topics: Temporal data in the data warehouse, especially in connection with data vault and dimensional modeling.

  • 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

    Data Vault im Einsatz beim Gutenberg Rechenzentrum

  • On July 15, Mathias Brink and I ran a webinar about Data Vault on EXASOL, modeling and implementation. The webinar started with an overview of the concepts of Data Vault Modeling and how Data Vault Modeling enables agile development cycles. Afterwards, we showed a demo that transformed the TPC-H data model into a Data Vault data model and how you can then query the data out of the Data Vault data model. The results were then compared with the original queries of the TPC-H.

  • 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.

  • I was at the Data Modeling Zone Europe 2016 in Berlin as a speaker. It was the 4th Data Modeling Zone in Europe and in my opinion one of the best per the conference program and the interesting and awesome chats with other speakers and attendees. This year’s venue was the Abion Hotel in Berlin, situated next to the Spreebogen and for this a great environment around the venue.

  • I reactivated my Meetup Data Vault Interest Group this week. Long time ago I was thinking about a table of fellow regulars to network with other, let’s call them Data Vaulters. It should be a relaxed get-together, no business driven presentation or even worse advertisement for XYZ tool, consulting or any flavor of Data Vault. The feedback of many people was that they want something different to the existing Business Intelligence Meetings. So, here it is!

  • FastChangeCo and the Fast Change in a Hybrid Cloud Data Warehouse with elasticity

    What is this 20 minute talk about at #BAS19?

    The fictitious company FastChangeCo has developed a possibility not only to manufacture Smart Devices, but also to extend the Smart Devices as wearables in the form of bio-sensors to clothing and living beings. With each of these devices, a large amount of (sensitive) data is generated, or more precisely: by recording, processing and evaluating personal and environmental data.