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Creating a Data-Driven Enterprise in Media

Book Description

The data-driven revolution is finally hitting the media and entertainment industry. For decades, broadcast television and print media relied on traditional delivery channels for solvency and growth, but those channels fragmented as cable, streaming, and digital devices stole the show.

In this ebook, you’ll learn about the trends, challenges, and opportunities facing players in this industry as they tackle big data, advanced analytics, and DataOps. You’ll explore best practices and lessons learned from three real-world media companies—Sling TV, Turner Broadcasting, and Comcast—as they proceed on their data-driven journeys.

Along the way, authors Ashish Thusoo and Joydeep Sen Sarma explain how DataOps breaks down silos and connects everyone who handles data, including engineers, data scientists, analysts, and business users. Big-data-as-a-service provider Qubole provides a five-step maturity model that outlines the phases that a company typically goes through when it first encounters big data.

Case studies include:

  • Sling TV: this live streaming content platform delivers live TV and on-demand entertainment instantly to a variety of smart televisions, tablets, game consoles, computers, smartphones, and streaming devices
  • Turner Broadcasting System: this Time Warner division recently created the Turner Data Cloud to support direct-to-consumer services, including FilmStruck, Boom (for kids), and NBA League Pass
  • Comcast: the largest broadcasting and cable TV company is building a single integrated big data platform to deliver internet, TV, and voice to more than 28 million customers

Table of Contents

  1. 1. Data-Driven Disruption in the Media and Entertainment Industry: Trends, Challenges, and Opportunities
    1. A Fragmented—but Growing—Industry
    2. How Data Is Changing the Media Game
    3. Three Areas of Opportunity for Media Companies
      1. New (Cloud) Infrastructure Required
      2. Artificial Intelligence: An Extraordinarily Promising Innovation
      3. Using Analytics to Drive True Personalization
    4. Initiating a Cultural Shift Across the Organization
    5. Getting the Industry Up to Speed
    6. Get in the Game, or Get Out
  2. 2. A Brief Primer on Data-Driven Organizations and DataOps
    1. The Emergence of DataOps
    2. The Data-Driven Maturity Model
    3. Where Are You in the Maturity Model?
  3. 3. Sling TV: Providing “Big Data on Demand” for Users and Systems
    1. Sling TV’s Current Data Landscape and Plans for Next-Generation Data Pipeline
    2. The Cloud as an Enabler of Infrastructure Elasticity
    3. Helping Users Help Themselves
    4. On Not Owning the Last Mile
    5. On Jumping into the Data Lake
    6. Using Data to Drive Business Decisions
    7. Encouraging a Data-Driven Culture
    8. Then There’s Automation…
    9. Starting on Your Journey
  4. 4. Turner Broadcasting Company: Dedicated to the Cloud for its Data-Driven Journey
    1. What Made Turner Turn Toward Data
    2. Moving up the Big Data Maturity Model
    3. The Evolution of the Turner Data Team
    4. Moving Toward User Self-Service
    5. Challenges and Next Steps
    6. Lessons Learned
  5. 5. Comcast: How a Focus on Customer Experience Led to a Focus on Data Science
    1. Why a Single Platform?
    2. How Data Is Used to Solve Business Challenges
    3. Why Governance Is Essential
    4. Team Interactions at Comcast T&P
    5. DataOps as a Way of Work
  6. 6. The Changing Data Landscape for Media, and Next Steps Toward Becoming Data Driven
    1. Three Industry-Wide Changes Compelling Media Companies to Become Data Driven
    2. The Changing Pace and Face of Content Distribution
      1. Proliferation of Devices and Connectivity
      2. Availability of Scalable and Cost-Effective Tools to Manage Big Data
    3. Adopting an Agile, Data-First Mentality
    4. Five Steps to Becoming Data Driven
      1. Hire Data Visionaries
      2. Consolidate Data into Cloud Data Lakes with Enterprise-Wide Access
      3. Empower All Employees
      4. Invest in the Right Self-Service Data Tools for Each Type of User
      5. Hold Employees Accountable
    5. In Conclusion