Description

Information Management: Gaining a Competitive Advantage with Data is about making smart decisions to make the most of company information. Expert author William McKnight develops the value proposition for information in the enterprise and succinctly outlines the numerous forms of data storage. Information Management will enlighten you, challenge your preconceived notions, and help activate information in the enterprise. Get the big picture on managing data so that your team can make smart decisions by understanding how everything from workload allocation to data stores fits together.

The practical, hands-on guidance in this book includes:

  • Part 1: The importance of information management and analytics to business, and how data warehouses are used
  • Part 2: The technologies and data that advance an organization, and extend data warehouses and related functionality
  • Part 3: Big Data and NoSQL, and how technologies like Hadoop enable management of new forms of data
  • Part 4: Pulls it all together, while addressing topics of agile development, modern business intelligence, and organizational change management

Read the book cover-to-cover, or keep it within reach for a quick and useful resource. Either way, this book will enable you to master all of the possibilities for data or the broadest view across the enterprise.

Key Features

  • Balances business and technology, with non-product-specific technical detail
  • Shows how to leverage data to deliver ROI for a business
  • Engaging and approachable, with practical advice on the pros and cons of each domain, so that you learn how information fits together into a complete architecture
  • Provides a path for the data warehouse professional into the new normal of heterogeneity, including NoSQL solutions

Readership

IT organizations/ vendors/consultants, DBAs, information architects, managers/directors of information management.

Table of Contents

Foreword

In praise of Information Management

Preface

Chapter One. You’re in the Business of Information

An Architecture for Information Success

The Glue is Architecture

Workload Success

Information in Action

Judgment Still Necessary

Chapter Two. Relational Theory In Practice

Relational Theory

Multidimensional Databases

RDBMS Platforms

Action Plan

Chapter Three. You’re in the Business of Analytics

What Distinguishes Analytics?

Predictive Analytics

Building Predictive Analytic Models

Analytics and Information Architecture

Analytics Requires Analysts

Action Plan

Chapter Four. Data Quality: Passing the Standard

Data Quality Defect Categories

Sources of Poor Data Quality

Cures for Poor Data Quality

Action Plan

Chapter Five. Columnar Databases

Columnar Operation

Compression

Workloads

Workload Examples

Columnar Conclusions

Action Plan

Chapter Six. Data Warehouses and Appliances

Data Warehousing

The Data Warehouse Appliance

Data Appliances and the Use of Memory

Action Plan

Chapter Seven. Master Data Management: One Chapter Here, but Ramifications Everywhere

MDM Justification

A Subject-Area Culture

Mastering Data

The Architecture of MDM

MDM Governance

Data Quality and MDM

MDM Roles and Responsibilities

MDM Technology

Action Items

Chapter Eight. Data Stream Processing: When Storing the Data Happens Later

Uses of Data Stream Processing

Data Stream Processing Brings Power

Stream SQL Extensions

In Conclusion

Action Plan

References

Chapter Nine. Data Virtualization: The Perpetual Short-Term Solution

The History of Data Virtua

Details

No. of pages:
214
Language:
English
Copyright:
© 2014
Published:
Imprint:
Morgan Kaufmann
Print ISBN:
9780124080560
Electronic ISBN:
9780124095267

About the editor

William McKnight

William is President of McKnight Consulting Group (www.mcknightcg.com). He is an internationally recognized authority in information management. His consulting work has included many of the Global 2000 and numerous midmarket companies. His teams have won several best practice competitions for their implementations and many of his clients have gone public with their success stories. His strategies form the information management plan for leading companies in various industries. William is a very popular speaker worldwide and a prolific writer with hundreds of articles and white papers published. William is a distinguished entrepreneur, and a former Fortune 50 technology executive and software engineer. He provides clients with strategies, architectures, platform and tool selection, and complete programs to manage information.

Affiliations and Expertise

President of McKnight Consulting Group

Reviews

From the Author: The Information Architecture To Pursue

A top priority of CIOs and organizations everywhere is how to best adapt the environment to manage the information asset. There is a plethora of available systems to throw into that equation. The possibilities can be daunting.

  • "One size fits all" does not apply to information architecture.
  • Gone are the days when vendors could bring their laminated architectures to a client with credibility.
  • Organizations must go forward incrementally from where they are and deliver business returns with each -- at the quarter-, not year-level, turnaround.

For such an important asset, the barometer cannot be a competitor’s environment. Early adopters of good practices will reap the most rewards. Following are several key actions to take to improve a company’s information architecture.

Move Key Operational Systems To In-Memory

In-memory for operational systems is appropriate wherever SQL is used operationally and the performance gains of in-memory can be utilized.

Configurations differ. Products like VoltDB are NewSQL systems purpose-built for storing data and throughput of transactional systems. NewSQL is used today for traditional high performance applications such as capital markets data feeds, financial trade, telco record streams, sensor-based distribution systems, wireless, online gaming, fraud detection, digital ad exchanges, and micro transaction systems.

NewSQL systems are in-memory, schema-based DBMS systems that scale out in a cluster. They have high availability architectures that use synchronous, multi-master, active-active replication. As the name implies, NewSQL supports full SQL – aggregate functions, LIKE, UNION, materialized views, indexes, etc.

In-memory also is found in DBMS environments that primarily scale-up like SAP HANA, Teradata, and IBM Pu