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Book Description

Fast access to data has become a critical game changer. Today, a new breed of company understands that the faster they can build, access, and share well-defined datasets, the more competitive they’ll be in our data-driven world. In this practical report, Scott Haines from Twilio introduces you to operational analytics, a new approach for making sense of all the data flooding into business systems.

Data architects and data scientists will see how Apache Kafka and other tools and processes laid the groundwork for fast analytics on a mix of historical and near-real-time data. You’ll learn how operational analytics feeds minute-by-minute customer interactions, and how NewSQL databases have entered the scene to drive machine learning algorithms, AI programs, and ongoing decision-making within an organization.

  • Understand the key advantages that data-driven companies have over traditional businesses
  • Explore the rise of operational analytics—and how this method relates to current tech trends
  • Examine the impact of can’t wait business decisions and won’t wait customer experiences
  • Discover how NewSQL databases support cloud native architecture and set the stage for operational databases
  • Learn how to choose the right database to support operational analytics in your organization

Table of Contents

  1. 1. How Data Drives Innovation
    1. The Evolution of Information
    2. The Data-Driven Company
    3. Key Advantages of the Data-Driven Company
  2. 2. The Rise of Operational Analytics
    1. Decision Making at the Speed of Business
    2. The Emergence of Operational Analytics
    3. “Can’t Wait” Data for Decision Making
    4. “Won’t Wait” Data for Customer Experiences
    5. Single Source of Truth
  3. 3. Challenges with Data Platform Infrastructure
    1. The Trouble with Building Up a Data Platform
    2. Database Types
      1. OLTP Databases
      2. OLAP Databases
      3. NoSQL Databases
    3. Special-Purpose Data Stores
      1. Data Warehouses
      2. Data Lakes
      3. Distributed File Systems
    4. Data Pipelines
    5. Spark and the Shift from Batch to Streaming
    6. Kafka Takes Streaming Further
    7. Achieving Near-Real-Time Capabilities for Data Transfer
  4. 4. NewSQL and Operational Analytics
    1. The NewSQL Revolution
    2. What Exactly Is NewSQL?
    3. A Brief Note on NewSQL and Database Theory
    4. The Operational Database and Operational Analytics
    5. Key Features of the Operational Database
      1. Zero Downtime
      2. Shared-Nothing Scale-Out
      3. Balance Consistency and Availability
      4. High-Performance Data Ingestion
      5. Fast Query Response Time
      6. Security to Stake Your Company On
    6. Use Cases
      1. Ecommerce
      2. Telecommunications
  5. 5. Selecting the Right Database for the Job
    1. The Road Ahead
    2. Database Selection Criteria
    3. Selection Criteria for Operational Analytics
      1. Integrations
      2. Automation
      3. Extensibility
      4. Machine Learning Automation
      5. Security
    4. NewSQL Offerings
      1. MemSQL
      2. Google Cloud Spanner
      3. CockroachDB
    5. Decision Time
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