Modern Data Architecture

In the last five years, digital transformation has reshaped data management presenting new challenges and opportunities including:

• Data complexity caused by many more data sources with data now stored in SaaS applications, on multiple Clouds, on-premises and streaming in from the edge
• Business units are buying Data Catalogs to help understand, govern and provision data
• Multiple new siloed analytical systems like streaming Analytics, Lakehouses and graph databases have appeared beyond the Data Warehouse offering alternative new Data Architectures
• Data Modelling seems to have disappeared
• Data engineering is now happening everywhere and new technologies like Data Fabric and Modern Data Stacks have emerged offering way more than ETL
  
  

Simultaneously CEO’s now see data and AI as strategic and needed in every part of the business. They are demanding a way forward to speed of development.

So how do you make sense of all this? Is there a future for the Data Warehouse? Is Data Modelling dead?  With so many competing Data Architectures, which one is best?  How do you meet all requirements and prevent chaos?

This new 2-day class looks at this problem.