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Introduction to Data Modeling

About This Course

The role of the data modeler has become even more critical to the ongoing lifecycle of development and maintenance, especially in this age of digital transformation. Analysts, developers, DBAs, and BI professionals need to develop their skills in analyzing and modeling data. Whether working with new or legacy data, you must define rules for quality, retention, and protection. And you need a good foundation of data and data design concepts before you begin sourcing, preparing, and manipulating data.

In this introductory course, learn how logical and physical data modeling can give you a better understanding of your organization's data, business rules, and information architecture decisions. Examine how data models are critical to your data security, privacy, and compliance posture. And get hands-on with real-world data—analyze it, implement business requirements, develop data models, and forward and reverse-engineer SQL Server databases.

Note: To complete the hands-on requirements, you’ll work with Office 365, Visual Studio, and Azure SQL Database. Free or limited-time trials are available for these products. You will require an Azure subscription. You can sign up for a free Azure trial subscription (a valid credit card is required for verification, but you will not be charged for Azure services). Note that the free trial is not available in all regions. It is possible to complete the course and earn a certificate without completing the hands-on practices.

prerequisites

A basic understanding of computers, a willingness to learn, and an ability to persevere and troubleshoot problems.

What you'll learn

  • Fundamentals of normalization and why it's important to transactional databases
  • How to develop logical and physical data models
  • How to model data security, privacy and protection requirements
  • When and where to model database-specific performance requirements
  • How model-driven development fits in a DevOps or agile environment
  • How to avoid schema drift and other data anti-patterns

Course Syllabus

Module 1: Introducing Data Modeling
Understand the business case for data modeling, and get an introduction to normalization, data modeling taxonomy, and model-driven database design.

Module 2: Designing Logical Data Models
Learn about identifying entities, attributes, and relationships, and learn about entity relationship diagramming and metadata capture.

Module 3: Designing Physical Data Models
Get the details on transforming a logical data model into a physical model, including designing database-specific features and constraints.

Module 4: Leveraging Data Models on Agile and DevOps Projects
Explore the process of data modeling on modern development projects, including planning, continuous delivery, test driven development, continuous integration, sprints, versioning, and deliverables.

Meet the instructors

Course Staff Image #1

Chris Randall

Senior Content Developer, Microsoft Learning Experiences

Microsoft

Chris is a trainer, consultant, and author with 25 years of industry experience, specializing in SQL Server and the Microsoft data platform. He is a Microsoft Certified Solutions Expert for the SQL Server Data Platform and Business Intelligence, and works in the Microsoft Learning Experiences team as a senior content developer, where he plans and creates content for developers and data professionals who want to get the best out of Microsoft technologies.

Course Staff Image #2

Karen Lopez

Sr. Project Manager and Architect

InfoAdvisers

Karen is a senior data architect with an extensive background in development processes and data management.She specializes in taking practical approaches to solutions development.

Karen has helped many IT organizations choose appropriate methods and standards based on the group’s culture, experience, and focus.She is an international speaker on modern development and design processes, specializing in engaging, often irreverent presentations on data and career-related topics. She blogs at datamodel.com and can be found on Twitter @datachick.

Karen is a Microsoft Data Platform MVP and wants you to love your data as much as she does.

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