Over time, things change - things like customers, products, accounts, and so forth. But most of the data we keep about things describes what they are like currently, not what they used to be like. When things change, we update the data that describes them so that the description remains current. But all these things have a history, and many of them have a future as well, and often data about their past or about their future is also important. Tom Johnston
Today, most data warehouses already store any kind of history of data. But what’s about events that took place at a different time than what the data warehouse represents to us? Or data that will be valid in the future? For example, future planned prices for products and goods or special prices for discount battles or sales promotions like the “Black Friday” in the United States.
What will I learn?
The Big Business Man smiled. "Time," he said, "is what keeps everything from happening at once. Ray Cummings, The Girl in the Golden Atom, novel (1922)
Dirk Lerner, the teacher of Temporal data in a fast-changing world! will focus in this class on methods and techniques for storing bitemporal data in a Data Warehouse and afterwards merging timelines of bitemporal data, e.g. Data Vault Satellites, to get data out of the Data Warehouse’s core layer. He will show bitemporal basics for a better understanding of loading data as well as the concepts to develop SQL queries to insert and update temporal data within a Data Warehouse. Finally, concepts to provide Star Schema Dimensions as non-, uni- or bitemporal objects will be shown.
At the first day of the Temporal data in a fast-changing world! training the attendees will understand the basic temporal concepts. They will practice to model uni- and bitemporal database objects with Data Vault and how to load bitemporal data into a Data Warehouse.
The second day of the Temporal data in a fast-changing world! training will focus on how to get data out of the Data Warehouse. How to merge timelines of Data Vault objects and provide temporal data within a Star Schema. The attendees will understand the concepts by doing a lot of practical exercises.
On both days real world examples will be shown and attendees will do several exercises and SQL-tutorials.
What is included?
Arrival, departure and overnight stay are not included in the training.
the training includes a course material set, an eBook and SQL examples to download as well as drinks, lunch buffet and snacks in the breaks. Of course, there is also plenty of room for exercises, discussions and questions.
Every participant has the exclusive opportunity to join the Temporal Data Alumni and participate in the Temporal Data Alumni Meetups.
Please, note: You need to take your own laptop into the course!
Who is the class for?
As a Data Architect, Business Analyst, Data Modeler, Data Vault Expert, ETL developer, Data Warehouse Manager, BI Expert or BI Consultant you will get most out of this class.
If you are in doubt get in touch with us!
Where will the trainings take place?
Public training classes will take place in Frankfurt, Hamburg, Munich, Stuttgart, Cologne and Berlin. If another city is interesting for you, please get in touch with us.
Inhouse training classes will be offered on request.
Why are we doing this?
Thanks to everyone who took place in one of our presentations about temporal data or has taken the time to contact us. Your positive feedback and success stories are what keep us striving to set up this training class and to get even better!
Dirk Lerner and his presentation on bitemporal modeling at first gave me a brain freeze. However, his explanation of using a Data Vault satellite to track changes over time and collapsing the changes into a dimension for analytics was not only a requirement for financial reporting in Germany but also quite ingenious. Peter Avenant, Varigence - My thoughts on the Global Data Summit
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. His explanation helps you designing good SQL to populate bitemporal Star Schemas.
Dirks presentation and explanation about bitemporal Data Marts is excellent! There are not many sources to quote about this topic. Juan-José van der Linden, DataDenken
On these conferences we presented or will present about temporal data:
- German Data Vault User Group - Zeiten im Data Warehouse - Von der Quelle bis zum Data Vault, 2014 (GER)
This one was the first public presentation about temporal data.
- World Wide Data Vault Consortium - Times in a DWH - From Source to Data Vault - ClientCase with Teradata, 2015 (USA)
- German Data Vault Usergroup - Bi-temporale Daten aus Data Vault in ein Star Schema transformieren, 2017 (GER)
- Global Data Summit - Bitemporal modeling for the Agile Data Warehouse, 2017 (USA)
- Data Modeling Zone Europe - Send bitemporal data from Vault to the Stars, 2017 (GER)
- TDWI conference - Send bitemporal data from Ground to Vault to the Stars, 2018 (GER)
- Data Modeling Zone Europe - Managing Time in Data Vault, 2018 (GER)
This year's conferences
- Data Modeling Zone US - Managing time in a Data Warehouse: How to design, insert and update (bi-)temporal data, 2019 (USA)
- Data Modeling Zone EU - Managing time in a Data Warehouse: How to design, insert and update (bi-)temporal data, 2019 (GER)
What is the training fee?
- You will receive 15% as an early bird discount on the original price (€2.270,00) as well as on the group rates until 22nd April 2019.
- The early adopter offer of €2.270,00 (without discounts) is valid for the training until the end of 2019.