Data Strategy
by Sid Adelman, Larissa Moss, Majid Abai
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Book Summary Information
Author: Larissa Moss, Majid Abai, Sid AdelmanEdition: Paperback
Audio: English (Unknown); English (Original Language); English (Published)
Published: 2005-06-25
ISBN: 0321240995
Number of pages: 384
Publisher: Addison-Wesley Professional
Book Reviews of Data Strategy
Book Review: An important subject in today's business world...
Summary: 4 Stars
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...
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