The Microsoft Modern Data Warehouse

October 27, 2015

Data Preparation

Must-Have Capabilities a DW Needs to Fit Modern BI and Analytics

The traditional data warehouse is under pressure from the growing weight of explosive volumes of data, the expansive variety of data types, and the real-time processing velocity of how data is being used. These changes are so seismic that Gartner reports, “Data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate data management system in IT is changing.“

This whitepaper provides a discussion of the necessary capabilities needed for DW to evolve to fit modern BI and analytics needs along with a look at the Microsoft modern datawarehouse solution. Included are case studies, an examination of Hadoop and various deployment options and hybrid scenarios.

  • The traditional data warehouse
    • Traditional data source, IT management
    • The advent of Web 2.0
    • Core business value: historical analysis and reporting
  • Key trends breaking the traditional data warehouse
    • Increasing data volumes
      • Case study: Hy-Vee Supermarkets
    • Real-time data
      • Case study: Direct Edge Stock Exchange
    • New sources and types of data
    • Cloud-born data
    • Logical information architecture
  • Evolve to a modern data warehouse
    • Data management and processing
    • Data enrichment and federated query
    • Business intelligence and analytics
  • The Microsoft Modern Data Warehouse
    • All volumes
      • Scale-out relational data
      • Scale-out non-relational data
      • Case study: Hy-Vee Supermarkets
    • Real-time performance
      • In-memory columnstore performance
      • Case Study: Bank of Nagoya
    • Any data
      • What is Big Data?
      • Common scenarios for Big Data
      • What is Hadoop?
      • Integration of Hadoop non-relational data
      • Case Study: Direct Edge Stock Exchange
  • Deployment options and hybrid solutions
    • Box software
    • Prebuilt appliance
    • Cloud-based deployment
  • Conclusion