Advanced Data Vault Modeling

The next step after the Data Vault Certification (CDVDM) is participation in the Advanced Data Vault Modeler Seminar & Lab by Genesee Academy.

This two-day training is open for all certified Data Vault Modelers who want to share their experience, stay informed of the latest developments regarding Data Vault Modeling and at the same time want to expand their knowledge by learning from best practices and ‘lessons learned’ that are put forward by other participants.

The focus of these interactive training days for experienced Data Vault Modelers is on real-life modeling cases. On the basis of group analyses different alternatives, that are available in the data collection approach from Data Vault Ensemble, will be exposed, considered, ranked and eventually classified and categorised based on best practices.

By participating in Advanced Seminar & Lab you will obtain an up-to-date and deeper insight in the different options that are now available in the data collection approach from Data Vault Ensemble.

 

 

 Duration:
2 days

Costs:
€ 1.795,00 excl. VAT

Participants:
max 25

Cluster:
Data Modeling

Planning:

  • Oct 24,25 ’22 (OnLine)

* Since 2009, Connected Data Academy takes care ofthe certification in the Netherlands and Belgium as a full-fledged partner of Genesee Academy.

General information

FOCUS
The focus of this course is modeling. In particular this course is focused on providing students a deeper understanding of the various options available within the Data Vault Ensemble modeling approach.

GOAL
The goal of this course is to enable data modelers and architects to make the most informed and best possible modeling decisions when establishing their specific modeling pattern in their organization.

APPROACH
This course follows an example-driven approach based on over a dozen real-life modeling cases. For each modeling scenario there is a business case that leads to a set of alternatives. Through interactive group analysis and discussions, and drawing on the experiences of the students in the class, the various alternatives are uncovered, considered, often ranked, and ultimately classified and categorized based on best practice considerations, pros & cons, and how appropriate they might be given the specific business scenarios.

TARGET AUDIENCE
This course if for data modelers, data architects, information modelers, and other data warehousing and business intelligence professionals who work with the design of conceptual, logical or physical data. Students attending this course should be certified CDVDM modelers, who have taken and passed the Data Vault certification exam.

UNIQUE VALUE
This course provides the unique opportunity to leverage decades of Data Vault modeling experience from around the World to gain a deeper understanding of Data Vault modeling and the impact of various different patterns. It also provides a venue for connecting with other modelers to share experiences, ideas, models, challenges, discoveries, and to work together towards a common better understanding of ensemble modeling.

Program

SELECTED TOPICS

  1. Modeling Events (and the role of links)
  2. Modeling Context Arrays (impact on satellite design)
  3. Modeling for Big Data, Cloud & Streaming Deployments (leveraging new platforms)
  4. Modeling UOW – Event based UOW (advanced link design)
  5. Modleing UOW – Keyed Instance UOW (hubs vs links)
  6. Modeling Address (context close to key)
  7. Modeling the BK in and EDW (dealing with lack of Enterprise Key – also include Anchor/Focal alternatives)
  8. Modeling the Shuttle for Fuzzy Integration (dealing with realistic integration)
  9. Modeling the SAT BOK (alternate, degenerate keys, etc.)
  10. Modeling for Personally Identifiable Information and Privacy (PID)
  11. Architecture – Defining and Deploying the RAW and BDV (establish approach)
  12. Ensemble Logical Form (ELF) and Virtualization (in memory)
  13. Modeling Automation – the Play Book (how and when to automate)

Our courses are conducted by experienced teachers who have gained experience in consultancy practice.

Teacher

  • Hans P. Hultgren
  • Remco Broekmans

Registration form Advanced Data Vault Modeling

PARTICIPANT

BILLING ADDRESS

REMARKS

Terms

15 + 10 =

 

*Terms

Cancellation by Connected Data Academy, represented by Connected Data Group B.V.: Connected Data Group will make every effort to allow training to take place but reserves the right to cancel training at any time. Connected Data Group is not responsible for costs incurred by the client as a result of the rescheduling or cancellation of the training. If a training course has been canceled by Connected Data Group, the client will be given the option to transfer the booking to another training course or to have the already paid course fee refunded.

Cancellation by the client: Cancellation is possible up to 5 working days before the start of the training, after which the full registration fee is due. In case of cancellation up to 20 working days before the start, no costs will be charged, in all other cases 50% of the registration fee is due. Cancellation must always be made in writing. The student has a 7-day cooling-off period after signing and can cancel without costs, unless the training has not been planned during this period.

Settlement and invoicing: Unless otherwise agreed and stated as a payment condition, invoicing of the total amount for the training takes place after booking. Payment of the full invoice amount must be made no later than 15 working days before the start of the training. Connected Data Group reserves the right to refuse participation in the training if the invoice is not paid on time. By submitting this form, you order the relevant training. There is a cooling-off period of fourteen days
For the other conditions, Connected Data Group applies the general conditions of FENIT (Filed with the Registry of the District Court in The Hague on June 3, 2003 under number 60/2003)

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Connected Data Academy | www.connecteddataacademy.com

ALSO IN-COMPANY

We offer a (made-to-measure) in-company training if there are multiple colleagues with the same learning objectives.