Building Better Data Models
You've been tasked with coming up with a data model for a
system. Where do you start? What do you need to know? What should you expect
from a solid data model?
In this webinar we'll look at:
- The process of converting
ideas and concepts into data structures.
- What normalization is and why
we use it.
- How to move from the logical
model to the physical model.
- What specifically to consider
when implementing a physical data model on SQL Server.
Armed with this information, you'll be able to start the
process of creating a data model or tweaking an existing data model. You'll also
have some areas to look for within SQL Server when a database with an
implemented data model isn't performing well.
In addition, we will look at how to build a data model in Azure Synapse
Analytics using erwin Data Modeler and cover how to build a Logical/Physical
data model in Azure Synapse Analytics, adding properties like tables, columns, indexes and
views to the model, sharing the data model in different types of reports and
collaborating on the data model with different teams.
Join us for this free webinar.
Thursday, October 28, 2021
1:00:00 PM EDT (New York) | 5:00:00 PM UTC
Brian Kelley is an author, columnist, Certified Information Systems Auditor (CISA), and former Microsoft Data Platform (SQL Server) MVP (2009-2016) focusing primarily on SQL Server and Windows security. Brian currently serves as a data architect as well as an independent infrastructure/security architect concentrating on Active Directory, SQL Server, and Windows Server. He has served in a myriad of other positions including senior database administrator, data warehouse architect, web developer, incident response team lead, and project manager. Brian has spoken at 24 Hours of PASS, IT/Dev Connections, SQLConnections, the Techno Security and Forensics Investigation Conference, the IT GRC Forum, SyntaxCon, and at various SQL Saturdays, Code Camps, and user groups.
Vani Mishra is a Director of Product Management for erwin Data Modeler by Quest, responsible for leading customer-facing and awareness efforts for erwin Data Modeling. She is actively involved with our Data Modeling customers to set the DM product vision, strategy, and roadmap based on customer and industry requirements. She has spent 19 years with the erwin Data Modeler, starting from the original product founders, Logic Works. Recently Vani worked for Princeton University where she was their lead architect in data architecture team. Vani is passionate about erwin DM and delivering solutions to customers. When Vani is not working, she likes to cook and spend time with her husband and two boys.
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