CDMP Exam Cram”

Best Practices Approach to Developing a Competency in Data Modeling

29-30 June 2021

Melbourne Business School, Carlton

Lloyd Robinson Data Modeling Workshops are recognized as the most comprehensive in the industry.

Certification is your path to joining others to further develop our profession We help you set yourself apart from the competition by holding an industry recognised certification which strengthens your skill set. We support your professional growth and your achievement of your goals, both personal and professional. It is targeted at anyone who wishes to pass their CDMP examinations at the Associate, Practitioner or Master’s level seminar covers the eleven knowledge areas of DMBOK version 2. Includes summaries of each chapter, sample questions, hints and tips on passing the exams. The CDMP cram session runs as a 2-day intensive study session. At the end of the second day you can undertake the 90-minute CDMP exam.

ASK Lloyd about CDMP Certification

2 Day Workshop

$ 2200
  • LIMITED PLACES. BOOK EARLY.

2 Day Workshop + DMZ Conference

$ 4360
  • A GREAT DEAL
SAVE $240

Association Package

$ 4140
  • 10% DISCOUNT
SAVE $460

About this Workshop

Data modeling is about understanding the data used within our operational and analytics processes, documenting this knowledge in a precise form called the “data model”, and then validating this knowledge through communications with both business and IT stakeholders. Underlying all successful applications is a robust and precise data model, and similarly, most software development failures are due to a lack of understanding of the data or data requirements.

A data model is, therefore, an essential part of applications development including forward engineering, reverse engineering, and integration efforts. Forward engineering means focusing on business requirements, whereas reverse engineering means modeling existing systems to drive the support, replacement, or customization of applications. Integration projects such as business intelligence efforts, data lakes, and master data initiatives, require a consistent holistic view of concepts such as Customer, Account, and Product.

Data Modeling Fundamentals contains two days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects.

Top 4 Objectives:

  • Understand the value that using data models can deliver in your organisation.
  • Determine how and when to use each data modeling component.
  • Build relational and dimensional conceptual, logical, and physical data models.
  • Incorporate supportability and extensibility features into the data model.

Workshop Pricing

Two Day Workshop $990

One Day Workshop Plus DMZ Conference $2450 save $440

Team discounts apply to groups registering from the same organisaztions

Academic registrations are available.

Partner member association member recieve

20% Discount

on DMZ Asia conference and workshop packages.

Workshop Pricing

Academic registrations are available.

Partner member association member recieve

20% Discount

on DMZ Asia conference and workshop packages.

Day 1

Modeling Basics:

Assuming no prior knowledge of data modeling, we work on our first case study to illustrate four important gaps filled by data models. Next, we explore data modeling concepts and terminology, and with a set of questions. We quickly and precisely build a data model, explaining each component and gain practice reading business rules. We will complete several exercises, including creating a data model based upon an existing set of data. 

You will be able to answer the following questions: 

  • What is a data model, and what characteristics make a data model an essential wayfinding tool?
  • What are critical skills for a data modeler?
  • Why is precision so important?
  • What three situations can ruin a data model’s credibility? 

You will also learn these concepts, terms and skills:

Concepts & Terms

  • Applying the 80/20 rule to data modeling
  • Entities, attributes, and relationships
  • Exclusive and non-exclusive subtypes
  • Candidate, primary, natural, alternate, and foreign keys
  • Surrogate keys
  • Cardinality and referential integrity
  • Recursion

Skills

  • Six questions to translate ambiguity into precision
  • How to “read” a data model
  • Asking the most important Questions when reviewing a data model
  • Use different modeling notations
  • Represent subtypes
  • Model hierarchies and networks
Day 2

Understanding conceptual, logical, and physical data models:

The conceptual data model captures a business need within a well-defined scope, the logical data model captures the business solution, and the physical data model captures the technical solution. Relational, dimensional, and NoSQL techniques will be described at each of these three levels.

We will also practice building several data models, and you will be able to answer the following questions:

  • How do relational and dimensional models differ?
  • What are the ten different types of data models?
  • Why are conceptual and logical data models so important?
  • What are four different ways of communicating the conceptual?
  • What are the six conceptual data modeling challenges?
  • What is the lure of NoSQL?
  • What are the advantages and disadvantages of going to “schema-less”?
  • What is MongoDB?

You will also learn these concepts, terms and skills:

Concepts & Terms

  • Concept and Question Templates  
  • Grain, base, and atomic on a dimensional 
  • Transaction, snapshot and accumulating facts  
  • Conformed dimensions 
  • Junk, degenerate, and behavioural dimensions  
  • Outriggers, measureless meters, and bridge tables  
  • A star schema and a snowflake 
  • The Attributes Template 
  • Aggregation and summarisation 
  • Slowly Changing Dimensions 
  • NoSQL and RDBMS 
  • Document, Column, Key-value, and Graph databases 
  • ACID and BASE  
  • Physical and implementation data models 

Skills

  • Use the five strategic conceptual modeling questions
  • Build a conceptual data model
  • Capture a program-level view of business questions
  • Navigate a dimensional data model
  • Leveraging the grain matrix
  • Apply the Normalization Hike
  • Use views, indexing, and partitioning to improve performance
  • Subtyping on a physical data model
  • Using denormalisation

About Lioyd Robinson

Lloyd Robinson is an authority on the practical development of data management implementation, having been certified as a business intelligence professional at the Master’s level by TDWI. Previously, Lloyd held roles with direct responsibility of budgets up to ₤50 million, executing projects across financial services, utilities, education and government across four continents. 

Lloyd brings over 20 years of experience in strategic, architecture and line management and is also experienced in delivering talks at key international conferences. Lloyd has comprehensive training in Benefits Management, ITIL, Enterprise Architecture, Program Management, Training and Counselling and demonstrates the exceptional qualities of diligence and patience in shaping a solution. 

Venue

Workshop Times

  • Registration 8.00 am
  • Workshop starts 8.30 am
  • Workshop close 4.30 pm

Lunch and refreshments are provided. 

What should I bring?

  • This is a participative workshop. A detailed handbook is provided complete with case studies.

Parking

  • The University Square Public car park is a 5-minute walk from the venue.
  • Casual Entry: $25.00 all day. 

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