San Francisco, CA: Apache Cassandra – Data Modeling
Date(s) - January 12, 2015 - January 13, 2015
Time -
All Day
Description: This course teaches conceptual, logical, and physical data modeling for Apache Cassandra. It covers intermediate and advanced, state-of-the-art data modeling methodologies, schema design optimizations, and indexing techniques.
Length: 2 days
Prerequisites: Completion of the Apache Cassandra: Core Concepts, Skills, and Tools course, or equivalent practical experience with Apache Cassandra.
Audience: Data architects, database designers, database administrators and database developers seeking to gain proficiency in data modeling and schema design for Apache Cassandra.
Environment: Virtual Machine pre-configured with Apache Cassandra, related tools, and exercise files.

Learning Objectives

Review of the Cassandra Data Model and CQL

  • Review CQL tables
  • Review CQL Data Definition Language
  • Review CQL querying capabilities

Conceptual Data Modeling

  • Overview conceptual data modeling techniques
  • Understand entity-relationship model

Logical Data Modeling

  • Introduce Chebotko Diagrams
  • Understand Cassandra data modeling principles
  • Introduce query-driven data modeling methodology
  • Master mapping rules
  • Master mapping patterns

Analysis and Validation of Logical Design

  • Review logical design analysis
  • Understand partition size limitations
  • Understand the cost of data redundancy and data consistency
  • Understand the cost of application-side joins and referential integrity constraints
  • Describe considerations for transactions and data aggregates

Physical Data Modeling and Optimization Techniques

  • Describe key design techniques
  • Describe table design optimizations
  • Understand secondary index use cases
  • Understand techniques for concurrent access to data

Selected Use Cases

  • Describe common Cassandra use cases
  • Model sensor data
  • Model messaging data