Data Strategy

Features

• Cover Type: Paperback with 384 pages
• Published by: Addison-Wesley Professional June 25, 2005
• Written in: English
• ISBN 10 Number: 0321240995
• ISBN 13 Number: 978-0321240996
• Book Dimensions: 9.1 x 6.8 x 0.8 inches
• Weighs: 1.2 pounds

Back Cover Copy


The definitive best-practices guide to enterprise data-management strategy.

You can no longer manage enterprise data "piecemeal." To maximize the business value of your data assets, you must define a coherent, enterprise-wide data strategy that reflects all the ways you capture, store, manage, and use information.

In this book, three renowned data management experts walk you through creating the optimal data strategy for your organization. Using their proven techniques, you can reduce hardware and maintenance costs, and rein in out-of-control data spending. You can build new systems with less risk, higher quality, and improve data access. Best of all, you can learn how to integrate new applications that support your key business objectives.

Drawing on real enterprise case studies and proven best practices, the author team covers everything from goal-setting through managing security and performance. You'll learn how to:

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  Identify the real risks and bottlenecks you face in delivering data-and the right solutions
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  Integrate enterprise data and improve its quality, so it can be used more widely and effectively
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  Systematically secure enterprise data and protect customer privacy
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  Model data more effectively and take full advantage of metadata
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  Choose the DBMS and data storage products that fit best into your overall plan
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  Smoothly accommodate new Business Intelligence (BI) and unstructured data applications
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  Improve the performance of your enterprise database applications
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  Revamp your organization to streamline day-to-day data management and reduce cost
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  Data Strategy is indispensable for everyone who requirements to manage enterprise data more efficiently-from database architects to DBAs, technical staff to senior IT decision-makers.

© Copyright Pearson Education. All rights reserved.

About The Author


Sid Adelman is a principal in Sid Adelman & Associates, an organization specializing in planning and implementing data warehouses, in data warehouse and BI assessments, and in establishing effective data architectures and strategies. He is a regular speaker at the Data Warehouse Institute and IBM's DB2 and Data Warehouse Conference. Sid also speaks often at DAMA conferences. He chairs the "Ask the Experts" column on http://www.dmreview.com.

Sid is a founding member of the Business Intelligence Alliance. Its members include Colin White, Herb Edelstein, Larry English, David Foote, Douglas Hackney, Pieter Mimno, Neil Raden, and David Marco. Sid is also a frequent contributor to journals that focus on data warehouse and data-related topics. He co-authored Data Warehouse Project Management with Larissa Moss. He is the primary author of Impossible Data Warehouse Situations with Solutions from the Experts.

Sid can be reached at sidadelman@aol.com. His web site is http://www.sidadelman.com.

Larissa Moss is president of Method Focus Inc., a corporation specializing in enterprise information management. She frequently lectures at data warehouse and data quality conferences worldwide on the topics of data warehousing, business intelligence, and other enterprise architecture and data strategy topics, such as data integration, data modeling, data quality, and metadata. Larissa is a senior consultant of the Cutter Consortium and a member of Friends of NCR-Teradata and the IBM Gold Group. Her present and past associations also include membership in DAMA, part-time faculty member at the Extended University of California Polytechnic University Pomona, associate of the Relational Institute and the Codd & Date Consulting Group, and lecturer for TDWI, DCI, MIS Training Institute, and PESG.

Larissa has authored and co-authored numerous books, white papers, and articles on business intelligence, project management, information asset management, development methodologies, data quality, and organizational realignments. She can be reached at methodfocus@earthlink.net. Her web-site is http://www.methodfocus.com.

Majid Abai is President of Seena Technologies, a Santa Monica, California consultancy dedicated to delivery of holistic data and enterprise solutions to various organizations. Majid's two decades of IT experience have been primarily focused on solution architecture, data strategies, and business intelligence systems for organizations facing challenges with the management of massive amounts of data. Majid has developed and teaches a class in Business Intelligence at the University of California, Los Angeles (UCLA) and several other seminars and lectures for national and international corporations. He can be reached at majid@seenatech.com. Seena Technologies website is http://www.seenatech.com.


© Copyright Pearson Education. All rights reserved.

Reader Reviews
With the recent spate of data privacy lapses, the subject of data within the organization is getting more visibility. One book that addresses the overall role of data is Data Strategy by Sid Adelman, Larissa Moss, and Majid Abai. Content: Introduction; Data Integration; Data Quality; Metadata; Data Modeling; Organizational Roles and Responsibilities; Performance; Security and Privacy of Data; DBMS Selection; Business Intelligence; Strategies for Managing Unstructured Data; Business Value of Data and ROI; ROI Calculation Process, Cost Template, and Intangible Benefits Template; Resources; Index The authors strike a nice balance between presenting solid information and keeping it readable. It's easy to get so wrapped in the subject of "data" that you lose the ability to make the concepts practical and realistic for today's organization. This book doesn't seem to fall prey to that tendency. They also cover the whole gamut of how data needs to be handled in an organization. A reader just starting out in IT would learn why integration is important, why data quality/consistency is paramount, and how to design a data model that can be used by multiple applications. A person who holds the title of "data analyst" or equivalent will probably know most of this information, but it might be a good refresher in some areas (like on how to manage unstructured data). The only issue I have with books like this is that they ignore the element of time and demand for application development. In every company I've worked at, there's always less time than required to do a "correct" job on the application design. There's also far more demand for applications than there are resources. If you're not careful, the demands of the data analysis group can paralyze an organization while they try to get everything "perfect". Meanwhile, nothing gets built. That's not to say that you can ignore all the information in this book. It's just that sometimes there are trade-offs you need to make in order to get things done in the real world. Even with that caveat, this is still a book I'd recommend to someone asking why they have to be concerned with the enterprise view of their data... Comment | | (Report this)