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.
- 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
IT organizations/ vendors/consultants, DBAs, information architects, managers/directors of information management.
In praise of Information Management
Chapter One. You’re in the Business of Information
An Architecture for Information Success
The Glue is Architecture
Information in Action
Judgment Still Necessary
Chapter Two. Relational Theory In Practice
Chapter Three. You’re in the Business of Analytics
What Distinguishes Analytics?
Building Predictive Analytic Models
Analytics and Information Architecture
Analytics Requires Analysts
Chapter Four. Data Quality: Passing the Standard
Data Quality Defect Categories
Sources of Poor Data Quality
Cures for Poor Data Quality
Chapter Five. Columnar Databases
Chapter Six. Data Warehouses and Appliances
The Data Warehouse Appliance
Data Appliances and the Use of Memory
Chapter Seven. Master Data Management: One Chapter Here, but Ramifications Everywhere
A Subject-Area Culture
The Architecture of MDM
Data Quality and MDM
MDM Roles and Responsibilities
Chapter Eight. Data Stream Processing: When Storing the Data Happens Later
Uses of Data Stream Processing
Data Stream Processing Brings Power
Stream SQL Extensions
Chapter Nine. Data Virtualization: The Perpetual Short-Term Solution
The History of Data Virtua
- No. of pages:
- © Morgan Kaufmann 2014
- 12th December 2013
- Morgan Kaufmann
- eBook ISBN:
- Paperback ISBN:
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.
President of McKnight Consulting Group
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