How to Choose Data Management Tools

30 June 2021

Two great workshops in one day!

A Practical Guide to Building a Data Stewards Network

1.30 pm to 05 pm

Melbourne Business School, Carlton

All newly created Chief Data Officer functions have the challenge of building an effective business data stewards’ network within their organisations. Potential stewards can range from having minimal data management experience to being very experienced but only for their business function. What a CDO must do is to get all Business Data Stewards onto the same page and focused on enterprise data processes. This half-day workshop sets out a practical, train-the-trainer approach for an eight-week program of training for business data stewards. At the end of the course, participants will be able to run a program of training within their organisation, building on training materials provided. The topics covered by the workshop are:
  • Introduction to data stewardship: why are they needed? What do they do?
  • Understanding the existing data landscape
  • Introduction to data governance, data quality, metadata and data modelling
  • Building requirements for data
  • The core data management competencies and training needs.

John Gray Data Modeling Workshops are recognized as the most comprehensive in the industry.

How to Choose Data Management Tools 

30 June 2021
9.00 am -12.30 pm
Melbourne Business School, Carlton

For small to medium-sized organisations, the selection of data management tools and repositories can appear to be a daunting and expensive task. Making choices can be challenging, especially when you feel a lot hangs in the balance. What tools are required?  Why do you need them? Who is going to use them?  What is their value? 

This workshop aims to demystify the decision making required around the selection of: 

  • Data Management Tools that support data management functions including data governance, data quality, data modelling, master data management, reference data, database development and data operations;  
  • Data Management Repositories used to store and disseminate the metadata generated by or managed by data management functions. 

Included is the workshop there will be a demonstration of the Erwin toolset. At the end of this half-day workshop participants will understand:

  • The different types of tools and the data management functions they support
  • The value each type of tool and how they work together
  • The relative benefits and disadvantages of selecting tools via tactical or enterprise approaches.

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

Partner association members receive 10% on DMZ Asia Pacific conference and workshop packages.

Academic registrations are available.

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 Half Workshop $990

DATA TOOL WORKSHOP Plus DMZ Conference $550 save $440

Team discounts apply to groups registering from the same organisaztions

Academic registrations are available.

Partner member association member recieve

10% 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

How to Choose Data Management Tools

1.30 pm to 5 pm

Melbourne Business School, Carlton

Understand the importance of leverage, and how to select tools to best position your data to achieve the most leverage for your orgnisation.

For small to medium-sized organisations, the selection of data management tools and repositories can appear to be a daunting and expensive task. Making choices can be challenging, especially when you feel a lot hangs in the balance.

What tools are required? Why do you need them? Who is going to use them? What is their value?

This workshop aims to demystify the decision making required around the selection of:

  • Data Management Tools that support data management functions including data governance, data quality, data modelling, master data management, reference data, database development and data operations.
  • Data Management Repositories used to store and disseminate the metadata generated by or managed by data management functions.

Included is the workshop there will be a demonstration of the Erwin toolset. 
At the end of this half-day workshop participants will understand:

  • The different types of tools and the data management functions they support
  • The value each type of tool and how they work together
  • The relative benefits and disadvantages of selecting tools via tactical or enterprise

About John Gray

Dr John Gray has 30 years of computing experience in across Australia and the UK in both industry and academia. Jon’s research interests have included parallel and distributed systems design, database technologies, information modelling, software engineering methods and tools, organisational capability development, and business process improvement. 

From 2006, Jon led a research initiative for National ICT Australia Limited (NICTA) in Canberra focused on software methods and tools for the improvement of business processes in government. He then led Performance Assurance, a spin-out company from NICTA from 2017, specialising in predictive modeling and risk management.  Jon is currently CEO & Chief Data Scientist for Catapult BI, a Dialog Group company. 

Jon has led numerous consulting engagements with across the Australian Government as well as in the NSW and QLD Governments, and large corporations such as Commonwealth Bank of Australia, Telstra, Optus, and NBN Co. Jon has extensive experience in planning, designing, and evaluating Business Transformation initiatives including enterprise architecture and SOA, ISR information systems integration, cloud migration, data centre consolidation, application portfolio rationalisation, legacy infrastructure retirement, and mainframe migration.   

Jon has published widely in many fields of software engineering, information systems, and computer science, and he is a frequent speaker at Australian and International conferences. 

Venue

Workshop Times

  • Registration 8.00 am
  • Workshop starts 1.30 am
  • Workshop close 5.00 pm

Morning Tea is 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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