An architecture based on Data Vault offers a unique solution, focused on data-integration by and in the whole organisation. The key to success for Data Vault lies in the flexible embeddedness of the company processes. Strict compliance with the fundamental rules of the concept guarantees a solid base for your datawarehouse. Data Vault offers the opportunity to realise flexible and cost effective datawarehouses in a short period of timeThrough a combination of on-line training and five intensive half-day on-site trainings you will receive answers to all your questions regarding Data Vault. The seminar will be rounded off with an exam which enables you to become ‘Certified Data Vault Data Modeler'.
COURSE OBJECTIVE:
• You understand all ins and outs of Data Vault, including the application of Big Data surroundings • You are able to put all principles into practice • You are fully prepared for the Certified Data Vault Data Modeler exam • You have done the exam on-site; you receive the results within four weeks
TARGET AUDIENCE:
• Data Architects • BI and/or IT architects • BICC team leaders • Business analysts • information analysts • data integration designers and consultants • ETL designers, project managers • database administrators • architects who are involved with Datawarehouse surroundings
COURSE PREREQUISITES:
Solid knowledge of Datawarehousing and some experience in the disciplines relevant for this seminar. Upon arrival in the class, participants must have *working knowledge* of Data Vault principles and standards as defined in the E-learning lessons.
COURSE CONTENT:
The CDVDM seminar consist of three components: • 8-10 hours of self-study via online video classes (e-learning). • 3 days of in-class lessons lead by a Genesee Academy Certified Instructor (on-site / live-on-line) • Certification exam (2,5 hours on-line exam in English). AD 1: ON-LINE / SELF STUDYFoundational Concepts – business overview • Segment 1: Architecture Constructs • Segment 2: Definition of the Data Vault • Segment 3: Issues and Evolution in Data Modeling • Segment 4: Scalability, Agility, Pros and Cons • Segment 5: Operational Data Warehousing • Segment 6: Business Case Studies • Segment 7: Common Business Process Modeling Errors • Segment 8: Classified Information Systems • Segment 9: Business Process Agility in I.T.Foundational Concepts – technical overviewSegment 1: Hubs & Lab on Hub Discovery • Hub Definition • Business Keys • Composite Business Keys • Real-time Arrival of KeysSegment 2: Links & Lab on Link Discovery • Link Definition • Link to Link • Links and Role Playing mistakesSegment 3: Satellites & Labs on Satellite Discovery • Satellite Definition • Type of Information • Rate Of Change • Splitting/Consolidating SatellitesKey Structures, Elements in Tables, Common Table StructuresSegment 4: Point in Time/Bridge Tables, User Defined/Record Sources • Point in Time Structures • Bridge Tables • Reference Structures • Report Collections • Net Change and Tracking data across loads • Aggregation PointsSegment 5: User Grouping Sets • Excel Sources • Flat File Sources • Defining User Data and processing into the DVSegment 6: EDW Processing • Business Processing Overview • Tying the business to the technical data models • The business process of defining a Data VaultSegment 7: Conversion to A Data Vault • Converting from Normalized format to a Data Vault • Converting a Dimension to a Data Vault • Converting from a Report to a Data VaultAD 2: IN CLASS TRAINNG Loading and Querying processes within a DVSegment 8: Golden Rules, Loading Constructs, math behind the Load Cycles • Golden Rule of the Data Vault • Basic Mathematics behind the loading processes • Paradigm Shift in executing Business Logic • Agility of the Loading Processes • Scalability of through Architecture • Hub, Link, Satellite Load Process FlowsSegment 9: Loading Data Delivery Mechanisms • Loading Dimensions • Loading Facts • Loading Error Marts • Loading Report CollectionsSegment 10: Scalability of Loading Processes • Issues with the current loading paradigm • Shifting the paradigm for Compliance reasons • Delta Processing and Set Logic • What to do about “bad data”Segment 11: What Happens when you Break the Data Vault Rules? • Role Playing Links • Mistakes with the Load DatesSegment 12: Business Constructs • SLA's needed for changes, and sign-off • Default Values versus Error Codes • Zero Rows populated in the Data Vault • Views in the Data VaultSegment 13: Strategies for Managing the Data Vault • Backup and Restore • Suggested Topic Areas • Suggested Satellites • Items To NoteExceptions & BrainstormNear the end of the seminar the inevitable “exceptions to the rule” will be discussed as well as other issues and specific challenges that have come up during the seminar. The seminar is concluded with a Data Vault recap, a brief time to prepare for the test and…the written exam.Free on-line in-depth modulesAfter the seminar you are able to extend your knowledge even further by accessing for two weeks additional in-depth on-line lessons through the e-learning program of Genesee Academy.AD 3: CERTIFICATION EXAMThe course will be completed, on a day to be determined (15.00 – 18.00 hours), with an online protored exam that allows you to become ‘Certified Data Vault Data Modeler'. The certification is a closed book exam and lasts 2,5 hours. The questions are in English and can be answered in English or Dutch.Within 4 to 6 weeks after the seminar you will receive the exam results. With a positive result you will also receive an official certificate of Genesee Academy. A free of charge resit exam is possible in consultation.
FOLLOW ON COURSES:
ADVM, Advanced Data Vault Modeling
