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TDWI Chicago Update

At TDWI, we have been working hard to navigate this ever-changing landscape in the face of COVID-19, and we want to assure you that the health and well-being of our employees, customers, and vendor partners is our top priority. Therefore, due to the growing concern around the coronavirus (COVID-19), and in alignment with the guidelines laid out by the CDC and WHO, we have decided to merge this year’s TDWI Chicago Conference (May 10-15) with TDWI Orlando 2020 (November 8-13), where it can be a successful experience for everyone. The Chicago 2020 agenda will be replicated at TDWI Orlando 2020.

Our registration team will be in contact with individual registrants and sponsors directly.

Course Description

Modern Data Management, Onsite, CBIP Certification, TDWI Foundations

TH2 TDWI Data Modeling: Data Analysis and Design for BI and Data Warehousing Systems

May 14, 2020

9:00 am - 5:00pm

Duration: Full Day Course

Level: Beginner to Intermediate

Prerequisite: This course assumes basic understanding of data warehousing fundamentals.

Aaron Fuller

CBIP

Principal and Owner

Superior Data Strategies LLC

Preview Course Materials Course Outline

Business intelligence and data warehousing systems challenge the proven data modeling techniques of the past. From requirements to implementation, new roles, uses, and kinds of data demand updated modeling skills. The data modeler’s toolbox must address relational data, dimensional data, unstructured data, and master data. For those with data modeling experience, this course extends their skills to meet today’s modeling challenges. Those new to data modeling are introduced to the broad range of modeling skills needed for BI/DW systems. Those who need to understand data models, but not necessarily develop them, will learn about the various forms of models and what they are intended to communicate.

You Will Learn

  • Differences in modeling techniques for business transactions, business events, and business metrics
  • Different types of data and their implications
  • Application of business context to modeling activities
  • The role of business requirements in BI data modeling
  • The role of source data analysis in data modeling
  • Use of normalized modeling techniques for data warehouse analysis and design
  • Use of dimensional modeling techniques for data warehouse analysis and design
  • The roles of generalization and abstraction in data warehouse design
  • The roles of identity and hierarchy management in data warehouse design
  • How time-variant data is represented in data models
  • Implementation and optimization considerations for warehousing data stores

Geared To

  • Data architects
  • Data modelers
  • BI program and project managers
  • BI and data warehouse developers