Diesmal beschäftigt sich das Team des Data Management Center of Excellence (DMCE) von FastChangeCo^TM mit der Frage: Was sind die geschäftlichen Anforderungen an bitemporale Daten?

This time, FastChangeCo^TM's Data Management Center of Excellence (DMCE) team looks at the question: what are the business requirements for bitemporal data?

With our TEDAMOH Academy we offer various seminars, trainings and workshops to support and develop continuous learning in your daily business.

You can either extend you theoretical knowledge by attending a seminar or work in practically oriented workshops to acquire knowledge by yourself. To train the usage of a new software or method, such as dealing with temporal data, it is best to have a closer look at the training area.

Or the battle announcement of the incoming interface

The BI Center of Competence (CoC) has decided to use bitemporal data storage when setting up a new data warehouse for one of the business units of the fictitious company FastChageCo™.

BI CoC is well advanced in the bitemporal implementation of Data Vault database objects as well as loading patterns. The already connected systems via formally defined incoming interfaces have worked without problems so far.

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.

Since more than 15 years I’m working with bitemporal data in Data Warehouse solutions. Meanwhile it is easy to design, build and populate tables for bitemporal data. But how to design and build bitemporal dimensional modeled Data Marts was new to me. Dirk Lerner does a very good job in explaining complex bitemporal stuff. 

Seit mehr als 15 Jahren arbeite ich mit bitemporalen Daten in Data Warehouse Lösungen. Mittlerweile ist es einfach, Tabellen für bitemporale Daten zu entwerfen, zu erstellen und zu befüllen. Aber wie man bitemporale dimensional modellierte Data Marts entwirft und aufbaut, war mir neu. Dirk Lerner leistet eine sehr gute Arbeit bei der Erklärung komplexer bitemporaler Daten.

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

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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:

Ich war sehr zufrieden mit Dirk Lerners Temporal Data in a Fast-Changing World! Training. Die Schulung hat alle meine Fragen zur Bitemporalität beantwortet, die in anderen Data-Vault-Schulungen nicht so klar angesprochen wurden.

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.

Ich hatte gerade bei einem neuen Kunden angefangen und war Teil des Data-Warehouse-Teams, das für den Aufbau des Data Warehouse mit Data Vault verantwortlich war. Wir hatten einen Data Vault-Generator entwickelt. Damals verwendeten wir ein Enddatum für die 'business timeline'. Ich erinnere mich, wie kompliziert es war, die alten Datensätze zu aktualisieren, und wie viel Zeit das den Server kostete. Vor allem, wenn man zwischendurch Datensätze hinzufügen wollte. Zum Beispiel um die Historie aus alten Quellen zu laden.

Does the Load Date Timestamp (LDTS) data element in the hub, link, or satellite capture the timestamp of the batch, or rather the transaction timestamp at which the data originated in the operational system?

Dirk hat eine sehr gut strukturiertes Training über temporale Daten durchgeführt. Er hat mir sehr geholfen, mein Wissen über dieses anspruchsvolle Thema zu erweitern.

Dirk provided a very well structured training on temporal data. He helped me a lot to increase my knowledge about this challenging topic.

At work I just started at a new customer and was part of the data warehouse team, who was assigned the task of building the Data Vault Data Warehouse. We were developing the Data Vault generator. At that point we used an end-date for the business time. I remember the complexity for updating the old records and the time for the server it costs to do this. Especially when you want to add rows in between. To load history, for example, from old sources. The training is led by Dirk in an interactive way.

We, Stephan and myself, are looking forward to welcome you at the TDWI Conference at the MOC Munich from June 24th - 26th, 2019! Meet us at our booth, discuss bitemporal topics, data vault or data modeling at all with us and attend one of Dirk Lerner's lectures:

• Model-driven decision making [Link], together with André Dörr and Mathias Brink
• FBI at Bosch - a real journey through the depth of "data water" [Link], together with Marc Wiesner, Director Finance BI Competence Center, Robert Bosch GmbH

• Temporal data series

  

   

  / SECRET SPICE - Temporal Data Series

  Temporal data - A time travel

  In loose order I publish my thoughts and experiences around bitemporal or more general temporal data. For me, this includes not only the properties and peculiarities of temporal data itself, but also the associated structures, loading processes and solutions of various kinds.

  In any case, important and not to be neglected are the business requirements that underlie all temporal data. From time to time in this series, I will show technologies and related examples that support temporal data.

  Like the already published series on PowerDesigner, this series is for myself a kind of diary, a knowledge base and the 'Secret Spice', in which I record my discoveries and for myself documented tips and tricks around temporal data. I would like to share this with you.

  And, as always, you'll meet team members from the Data Management Center of Excellence (DMCE) at my favorite client: FastChangeCo^TM!

• Temporale Daten Serie

  

   

  / SECRET SPICE - Temporale Daten Serie

  Temporale Daten - Eine Zeitreise

  In loser Folge veröffentliche ich meine Gedanken und Erfahrungen rund um bitemporale oder genereller temporalen Daten. Dazu gehört für mich nicht nur die Eigenschaften und Eigenheiten der temporalen Daten an sich, sondern auch die zugehörigen Strukturen, Ladeprozesse und Lösungsansätze unterschiedlichster Art. 

  Auf jeden Fall wichtig und nicht zu vernachlässigen sind die Geschäftsanforderungen, die allen temporalen Daten zugrunde liegen. Ab und an zeige ich in dieser Serie Technologien und dazu passende Beispiele, die temporale Daten unterstützen.

  Wie auch die bereits veröffentliche Serie zum PowerDesigner, ist diese Serie für mich selbst eine Art Tagebuch, eine Wissensbasis und das ‘Secret Spice’, in der ich meine Entdeckungen und meine für mich selbst dokumentierten Tipps und Tricks rund um temporale Daten festhalte. Daran möchte ich euch teilhaben lassen.

  Und ihr trefft wie immer auf Team-Mitglieder des Data Management Center of Excellence (DMCE) bei meinem liebsten Kunden: FastChangeCo^TM!