Introduction to NoSQL for Those Used to SQL: Storing and Managing Operational Big Data (NEW) in Riyadh Jeddah Makkah Madinah Khobar Saudi Arabia KSA

In this informative session, learn about the emerging class of NoSQL technologies that can be used to manage operational big data. Understand the ideal workloads for NoSQL in managing enterprise data, and where NoSQL adds value to an enterprise information strategy.

Find out how to get projects started, and how to drop the “not in production” label to position NoSQL as part of your production toolbox for data management.

We live and work today in a highly connected world where individuals and their relationships, brand perceptions, and consumer behaviors have become critical business success factors. Where patterns are involved in relationships, it is imperative to understand them. Graph databases are the technology that is best-suited to determining and understanding data relationships and the real-world relationships that they represent.
This class is an introduction to graph databases and the relationship data stored in them. It will help the student determine why, how, and where to apply graphs and how to get started.

This “code-lite” session addresses the NoSQL community as well as the key user community, providing guidance on how NoSQL technologies work and how to position them in the enterprise. This practical session will help you add a significant class of technologies into consideration to ensure information remains an unparalleled corporate asset.

You Will Learn

  • Big data basics
  • Enablers for NoSQL
  • NoSQL data models: key-value, document
  • Realizing Value from Relationship Data
  • Graph Database Modeling Basics
  • Graph Databases in the Enterprise: Data loading and architecture basics
  • NoSQL usage patterns
  • NoSQL database architectures

Geared To

  • Anyone with a SQL background who is interested, curious, or even skeptical about the role and value of NoSQL technologies.
  • Data architects
  • Business analysts
  • Data developers
  • Data administrators
  • Data strategists
  • Chief data officers

Technical resources.

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