Implementing Analytics

Implementing Analytics

A Blueprint for Design, Development, and Adoption

1st Edition - May 6, 2013

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  • Author: Nauman Sheikh
  • eBook ISBN: 9780124016811
  • Paperback ISBN: 9780124016965

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Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics.

Key Features

  • Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology
  • Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning
  • Helps formalize analytics projects from staffing, technology and implementation perspectives
  • Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process


Data warehouse professionals, data architects, IT managers, business professionals in data-intensive jobs, business and financial analysts, project managers

Table of Contents

  • Acknowledgments

    Author Biography


    Organization of Book


    Part 1: Concept

    Chapter 1. Defining Analytics

    The Hype

    The Challenge of Definition

    Analytics Techniques

    Conclusion of Definition

    Chapter 2. Information Continuum

    Building Blocks of the Information Continuum

    Information Continuum Levels


    Chapter 3. Using Analytics


    Customer Relationship Management

    Human Resource

    Consumer Risk



    Higher Education


    Energy and Utilities

    Fraud Detection

    Patterns of Problems

    Part 2: Design

    Chapter 4. Performance Variables and Model Development

    Performance Variables

    Model Development

    Champion–Challenger: A Culture of Constant Innovation

    Chapter 5. Automated Decisions and Business Innovation

    Automated Decisions

    Decision Strategy

    Decision Automation and Intelligent Systems

    Strategy Evaluation

    Champion–Challenger Strategies

    Chapter 6. Governance: Monitoring and Tuning of Analytics Solutions

    Analytics and Automated Decisions

    Audit and Control Framework

    Part 3: Implementation

    Chapter 7. Analytics Adoption Roadmap

    Learning from Success of Data Warehousing

    The Pilot

    Chapter 8. Requirements Gathering for Analytics Projects

    Purpose of Requirements

    Requirements: Historical Perspective

    Requirements Extraction

    Chapter 9. Analytics Implementation Methodology

    Centralized versus Decentralized

    Building on the Data Warehouse


    Chapter 10. Analytics Organization and Architecture

    Organizational Structure

    Technical Components in Analytics Solutions

    Chapter 11. Big Data, Hadoop, and Cloud Computing

    Big Data


    Cloud Computing (For Analytics)


    Objective 1: Simplification

    Objective 2: Commoditization

    Objective 3: Democratization

    Objective 4: Innovation



Product details

  • No. of pages: 234
  • Language: English
  • Copyright: © Morgan Kaufmann 2013
  • Published: May 6, 2013
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9780124016811
  • Paperback ISBN: 9780124016965

About the Author

Nauman Sheikh

Nauman Sheikh is a veteran of the data architecture profession who has built dozens of large scale operational and analytical systems over the last 18 years. He has worked in three continents solving business challenges in consumer credit, risk, fraud and direct marketing areas dealing with a variety of cultural, technological and legal challenges surrounding data and its use. He is a hands-on practitioner with skills ranging from analytical reporting to data mining models to analytics driven business decisions and their audit and control frameworks.

Affiliations and Expertise

Nauman Sheikh is a veteran of the data architecture profession who has built dozens of large scale operational and data warehouse systems over the last 17 years.

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