DATA MODELING COURSE

DATA VAULT MODELING & CERTIFICATION

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Data Modeling: Operational, Data Warehousing & Data Marts

CDVDM: Certified Data Vault Data Modeler Seminar

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COURSE DESCRIPTION
Learn data modeling in this comprehensive and dynamic course. Two days covers data modeling for operational systems, data warehouses, data marts and big data deployments. Great for business analysts, data architects, data modelers, data scientists, master data project teams, and data integration specialists. No prior modeling experience required.
This course will guide you through the Data Vault modeling approach from modeling constructs and patterns to applying data vault principles in your DWBI program. This course also covers loading paradigms, architectures, and how to develop an effective overall data vault data warehouse program. This course also includes a summary of the benefits of using data vault techniques.
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COURSE STRUCTURE & FEES
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Course includes two (2) days of classroom lecture, interactive labs and small group modeling exercises.
Course includes two (2) days of classroom lectures, interactive labs, certification exam and all materials.
Course includes three (3) days of classroom lectures, interactive labs, certification exam and all materials.
Have a group of 3 or more from the same organization or company? Register as a group and receive a discounted rate. Please tell us the number of students when you register.

Course Overview

This course covers the data modeling techniques related to each of three major area: Operational Systems, Data Warehouses, and Data Marts.

3NF Modeling. Beginning with the core fundamentals of database design including identifying the core entities and relationships, creating logical model designs, defining attributes and key structures, and developing entity relationship diagrams (ERDs). Within the scope of this modeling approach, the lessons will cover business rules, normalization, validation rules, reference tables, key constraints, identifying and non-identifying relationships, recursive relationships, redundancy, subtypes and supertypes, and relationship cardinality. Students will become comfortable with the core rules and best practices approach to 3NF modeling.

DataVault Modeling. The training will continue with the fundamentals of data warehouse modeling for the enterprise data warehouse (EDW). Within this section the core concepts of data warehousing are presented including the focus on integrated, non-volatile, time-variant and subject oriented data. The Data Vault modeling approach is presented including business keys (Hubs), relationships (Links) and context/history (Satellites). The course continues with core business concepts, ensembles, unified decomposition, concept constellations, and natural business relationships. The course considers how to model the data warehouse, agility, auditability, and data integration. This section also covers Big Data modeling considerations.

Dimensional Modeling. Next the training will cover dimensional modeling based on current best practice interpretations of the Kimball Star Schema dimensional modeling approach. Beginning with the fundamentals of dimensional modeling including the purpose and structure of Facts and Dimensions, denormalization, Slowly Changing Dimensions (SCDs) and the main Dimension Types (Type 2 and also covering Type 0, 1, 3, 4 and 6), then modeling and design of solid dimensions and encouraged forms of Star Schemas. The course continues with Snow Flake models, the encouraged and acceptable practices for deploying these concepts. Lastly, the course will cover physical data model considerations and DW/BI deployment topics.

Target Audience. The Target Audience for this class includes Business Analysts, Data Analysts, Data Modelers, Data Scientists, DWBI Managers, Data Architects, and Database/Data Warehouse Designers.

Data Vault modeling is rapidly becoming the standard modeling approach for the data warehouse. Over 800 major international companies are applying data vault modeling techniques today.

Principles. The data vault principles are specifically well suited for data warehousing programs and can provide the organization with some very compelling benefits. These include auditability, agility, adaptability, alignment with the business, and support for operational data warehousing initiatives.

Benefits. To gain these benefits the organization will need to commit to both EDW program level factors as well as specific data vault modeling patterns, rules and methods. This course will guide you through these modeling patterns, rules and methods to prepare you for active data vault modeling in your organization.

Certification. Upon successful completion of this course will result in a designation of Certified Data Vault Data Modeler – CDVDM. The CDVDM certification exam is administered in the classroom during the final afternoon of the course.

Target Audience. The target audience for this course includes data warehousing and business intelligence professionals, data modelers, data architects, model managers, data warehouse DBAs, and ETL professionals. Because data vault modeling concepts are closely aligned with the business aspects of DWBI programs our target audience also includes program managers, business analysts, information modelers, information architects, BICC professionals, and data scientists.

About the Instructor. Hans Hultgren is an advisor, trainer, author and industry analyst in the data management and data warehousing space. Hans has over 25 years experience in the industry and has taught data modeling concepts to thousands of students. Antoine is a Managing Consultant and Lead Architect of Business Intelligence at Centennium. He joined the management team in 2010 and is responsible for business development, sales and the overall quality of Centennium's services and deliverables. He combines his management role with client engagements as a lead architect and senior BI consultant. Remco Broekmans is a senior BI advisor, BI architect, coach and trainer with broad experience in data warehousing and business intelligence with a focus on the customers view on information and data modeling (Ensemble/ Data Vault).

Course Summary

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Instructor:
Hans Hultgren
About
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Antoine Stelma
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Remco Broekmans
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Course Downloads:

Course Schedule

Day 1

8:30 AMWelcome & Introductions
9:00 AMData Warehouse Modeling
9:30 AMEnsemble Modeling for the DW
10:00 AMData Vault Hubs, Links, Sats
10:20 AMException Constructs
10:30 AMBreak
10:45 AMData Vault Modeling
11:15 AMCase 1: Small Group Modeling Lab
12:00 PMBreak for lunch
1:00 PMContinue First Case
1:30 PMPresentations & Discussion
2:00 PMLink Design
2:15 PMCase 2: Small Group Modeling Lab
3:00 PMBreak
3:15 PMContinue Case 2 Group Lab
4:00 PMPresentations & Discussion
4:30 PMReference Tables
4:40 PMBusiness Key Modeling
4:50 PMNew EDW Requirements
5:00 PMEnd of day one: Q&A

Day 2

8:30 AMCoffee & Discuss Day One
9:00 AMWhy Data Vault for DW
9:15 AMSatellite Design 
9:45 AMUnit of Work with Discussion
10:30 AMBreak
10:45 AMCase 3: Small Group Modeling Lab
12:00 PMBreak for lunch
1:00 PMContinue Case 3 Group Lab
2:00 PMInterim Case Reviews
2:30 PMPresentations & Discussion
3:00 PMBreak
3:15 PMRaw and BDV Layers
3:35 PMAligning Business Keys
3:50 PMHelpful Tables: PIT
4:00 PMHelpful Tables: Bridge
4:10 PMHyper Forms & Unstructured
4:30 PMSID versus Hash
4:40 PMVirtulaization
4:50 PMWrap up day two: Q&A
5:00 PMHappy Hour

Day 3

8:30 AMCoffee & Discuss Day Two
9:00 AMWorking with Data Vault
9:30 AMData Vault & Agility
10:00 AMData Vault & Big Data
10:15 AMBusiness Key Topics
10:30 AMBreak
10:45 AMLoading Patterns
11:00 AMSatellite Design & Address
11:15 AMCommon & Mandatory Atts
11:30 AMClass Discussion
11:45 AMRecap for Ex AM
12:00 PMBreak for lunch
1:00 PMRecap & Discussions
1:30 PMCertification Ex AM
3:15 PMBreak
3:30 PMContinue Ceritifcation
5:00 PMCollect Exams/Course Completed
  
  
  

Day 1

8:30 AMWelcome & Introductions
9:00 AMData Vault Fundamentals
9:20 AMBusiness Justification: DV Benefits
9:30 AMEnsemble Modeling for the DW
9:40 AMUnified Decomposition
9:50 AMComparing 3NF, Dimensional & DV
10:05 AMData Vault Modeling Process
10:15 AMCore Constructs: Hub, Link, Satellite
10:30 AMBreak
10:45 AMCase 1 Small Group Exercise
11:45 AMPresentations & Discussion
12:15 PMLunch
1:00 PMCore Business Concepts & Bus Key
1:15 PMMethodology & DW Industry
1:25 PMFundamental Architecture
1:35 PMConcept Integration RAW vs BDV
1:45 PMError Marts & DWBI Feedback Loop
1:50 PMArchitectural Layers & Persistence
2:00 PMSAL/HAL, Codes & Reference Tables
2:15 PMCase 2 Small Group Exercise
3:00 PMBreak
3:15 PMComplete Case 2 Exercise
3:30 PMPresentations & Discussion
4:00 PMLink versus Hub Bike Shop Scenario
4:20 PMUnit of Work (UOW)
4:40 PMEnd of Day One: Q&A
4:55 PMAssign Case 3 Exercise
5:00 PMWrap up for the Day

Day 2

8:30 AMCoffee & Discuss Day One
9:00 AMCase 3 Small Group Exercise
10:30 AMBreak
10:45 AMPresentations & Discussion
11:15 AMIntegration Case Take Away Recap
11:30 AMModeling Addresses
11:40 AMSatellite Design & Cardinality
11:50 AMCommon & Mandatory Attributes
12:00 PMPIT & Bridge Tables
12:15 PMLunch
1:00 PMData Vault Loading Paradigm
1:15 PMSourcing Data from the DV DW
1:30 PMWrap Up & Exam Prep
2:00 PMCertification Exam
3:00 PMBreak
3:15 PMContinue Certification
4:45 PMCollect Exams
5:00 PMClass Completed

Day 1

08:30Arrive, Coffee and Introductions
09:00Introduction to Data Management
09:30Data Modeling Primer
10:15Break
10:30Beginning with the Operational
12:00Lunch
13:00Modeling Lab: 3NF
14:30Break
14:45Moving to the Dimensional Model
16:00Modeling Lab: Star Schema
17:00End of Day 1

Day 2

08:30Arrive, Coffee and Introductions
09:00Star Schema Modeling Lab Presentations
09:30Recap Day One Material
09:45Dimensional Modeling and the DW
10:15Break
10:30Data Modeling for the EDW
12:00Lunch
13:00Modeling Lab: Ensemble Data Vault
14:30Break
14:45Data Vault Lab Presentations
15:30Data Modeling – putting it all together
16:30Course Wrap Up
15:00Class Dismissed

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