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2-Day Seminar
Data Modelling Fundamentals
Build a Foundation in Data Modelling Concepts and Techniques
Register On-line:
20-21 September 2010, London
1-2
March 2011, London
Click
Here To Download The .PDF Brochure
- Overview
- Learning Objectives
- Seminar Outline
- Audience
- Speaker Biography
- Testimonials
- Seminar Fee
- Group Booking and Series Discounts
- Hotel Venue and Accomodations
Click here for an in-house quote request or for further information regarding in-house training.
Overview
Data Modelling Fundamentals contains a complete explanation of data
modelling concepts and terminology, along with techniques for producing
solid relational and dimensional data models. This course is designed
to give you a practical understanding of data modelling that can be
applied to your current projects.
- Data modelling concepts and terminology
- How to read a data model
- Steps to building a subject area model
- Logical data modelling techniques of normalization, abstraction, and dimensionality
- Physical data modelling techniques of denormalization, partitioning, views, and indexing
Modelling Basics
Assuming no prior knowledge of data modelling, we will begin this section with
an entertaining exercise that will illustrate an important gap filled by data
models. Next we will explain data modelling concepts and terminology. We will
also explore each component on a data model and practice reading business rules.
Here are the "Top 10" questions that will be answered in this part of the course:
- What is a data model and why is a piece of paper with boxes and lines so valuable to our organizations?
- How does a data model improve communication during the analysis process and after the model is complete?
- What two situations can degrade a data model's precision?
- What are five key skills every data modeler should possess?
- What do a data model and a camera have in common?
- What are entities, data elements, domains, and relationships?
- Why subtype and what are the four subtype types?
- What are the different types of keys on a model?
- Explain cardinality and how to read the relationships on a data model.
- What is recursion and why is it such an emotional topic?
Subject Area Modelling
A subject area model provides a broad high-level picture of an application,
business, or industry. Here are the "Top 10" questions that will
be answered in this part of the course:
- What is a subject area and what is definitely not a subject area?
- Why build a subject area model?
- What are the three types of subject area models?
- How do relational and dimensional subject area models differ?
- Describe the three approaches used to build subject area models.
- Where does subject modelling fit within a data management framework?
- What challenges exist in building a subject area model?
- What tips can help with subject area modelling?
- What business and IT roles are critical for building the subject area model?
- Which roles will most benefit from the subject area model?
Logical Data Modelling
A logical data model represents a business solution independent of
technology. Here are the "Top 10" questions that will be answered
in this part of the course:
- What is a logical data model?
- How do relational and dimensional logical data models differ?
- Discuss the strict modelling constraints placed on the dimensional model.
- Why do we have a love/hate relationship with dimensional models?
- What is normalization and why is it so great?
- Why is abstraction dangerous?
- Describe the three approaches used to build logical data models.
- What business and IT roles are critical for building the logical data model?
- Which roles will most benefit from the logical data model?
- Why do we often skip the logical data modelling phase and when do we pay the price?
Physical Data Modelling
A physical data model represents a technical solution dependent on
technology. Here are the "Top 10" questions that will be answered
in this part of the course:
- What is a physical data model?
- Explain the difference between a star schema, snowflake, and starflake.
- Where should denormalization be performed on your models?
- What are the five different ways of denormalizing?
- Where should views be chosen over denormalization?
- Why is indexing the modeler's best friend?
- Explain vertical and horizontal partitioning.
- Describe the three approaches used to build physical data models.
- What business and IT roles are critical for building the physical data model?
- Which roles will most benefit from the physical data model?
Audience
This course is for anyone who needs formal data modelling training.
This includes those new to data modelling or in need of a refresher who
need to be able to understand, build, or implement data models as part
of their job. Roles include:
- Data Modeller
- Data Architect
- Data Analyst
- Data Manager
- Enterprise Architect
- Information Architect
- Solutions Architect
- Applications Architect
- IT Consultant
- Business Analyst
- Project Manager
- Programme Manager
- Developer
- Senior Designer
- Data Administrator
- Database Administrator
- Data Quality Manager
- Data Steward
Special Features
- Attendees receive a copy of Steve Hoberman's newest book, Data Modeling Made Simple.
IIBA Accreditation
This course has been endorsed by The International Institute of Business Analysts. As such, this course has been approved as being aligned to the Business Analysis Body of Knowledge (BABOK) and hence are recommended training for business analysts who wish to sit the exam to become Certified Business Analysis Professionals (CBAP). For further information on how to register for the CBAP examination please refer to certification at www.theiiba.org.
|
Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modelling. He has worked as a business intelligence and data management practitioner and trainer since 1990, and is a popular and frequent presenter at industry conferences, both nationally and internationally. Steve is a columnist and frequent contributor to industry publications, as well as the author of Data Modeler's Workbench and Data Modeling Made Simple. He is the founder of the Design Challenges group and inventor of the Data Model Scorecard™. |
Seminar Fee
£1,095 + VAT (£191.63) = £1,286.63
Hotel Venue
and Accomodations
20-21 September 2010
Venue: Crowne Plaza London Kensington, 100 Cromwell Rd, London SW7 4ER
Tel: +44 (0)20 7373 2222 Fax: +44 (0)20 7373 0559
www.cpkensington.co.uk
1-2 March 2011
Venue: TBA London
London Accommodation: IRM UK in
association with JP Events Ltd has arranged special discounted rates
at all venues and at other hotels nearby the venue. Please visit the
JP Events website for further
information.
E-mail: enquiries@jpeventsltd.com Tel
+44 (0)84 5680 1138 Fax +44 (0)84 5680 1139.
In-House Training
If you require a quote for running
this course in-house, please contact us with the following details:
- Subject matter and/or speaker required
- Estimated number of delegates
- Location (town, country)
- Number of days required (if different from the public course)
- Preferred date
Please contact:
Jeanette Hall
E-mail: jeanette.hall@irmuk.co.uk
Telephone: +44 (0)20 8866 8366
Fax: +44 (0)1923 828 770
Speaker: Steve Hoberman
Endorsed by |
| DAMA International |
|
Endorsed by |
 |
Data Modelling Fundamentals is an endorsed course by the IIBA |
Group Booking Discounts
If 5 delegates from the same organisation register at the same time
for the same or various seminars, then the 5th delegate is free.
We regret that this offer cannot be used in conjunction with the
Series Discount.
Series
Discounts
Attend more than one course in this series and you will be entitled
to the following discounts:
- 2nd course 10%
- 3rd Course 15%
- 4th Course 20%
Data Management Series
Data Modelling Fundamentals
Successful Master Data Management
New Technologies and Architectures for Data Warehousing and Business Intelligence
Information Quality Improvement