Customer Reviews

Data Strategy

5 star:		(4)
4 star:		(2)
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1 star:		(1)

 

 

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...

Data Strategy doesn't really deliver what it promises. The book starts out hopeful, but then you keep wondering when the 'data-strategy part' is going to materialze. It doesn't.

What DOES the book offer? In various disciplines surrounding database management, data warehousing, data quality, etc. the authors have loads of experience and truly valuable advice. The book comes packed with all sorts of checklists which some may find useful (I didn't care for them so much). These people have clearly been around, and share quite some of their experience with the reader.

Sid Adelman, Larissa Moss, and Majid Abai have written an excellent book, one of the first that addresses the subject of data strategy in an organization.

The authors discuss various subjects within data that should be addressed by each and every organization. I was specially intrigued by the chapter on unstructured data as they are one of the first set of authors who have addressed unstructured data as part of the overall data within the organization. In addition, the chapters on business intelligence, data quality, and metadata address issues long needed in various size organizations.

A number of suggestions in the book apply mostly to medium-size and larger organizations, but the smaller companies could also take advantage of a lot of information contained in the book as they could sidestep some issues that exist within larger organizations.

I think authors have done an outstanding job in this book and I will certainly recommend it as a must read for all data professionals as well as CIOs, CTOs, and Enterprise Architects who are planning to create an information-centric organization.

As an IT salesperson, I wanted to know more about the data issues that my customers deal with. This book was perfect for that. I was pleasantly surprised at how readable it is, and with a minimum of "filler." It almost reads like an internal best practices document that an IT consulting firm might use (and closely guard). All concepts are explained thoroughly and with good examples. I thought all the check-off lists were particularly useful. But since I'm not an IT practitioner myself, I wouldn't be able to use them directly, but at least it achieved the goal of helping me better understand what my customers go through. Especially the intro, data integration chapter, and sections on how to deal with vendors and ROI/cost benefit analysis.

One of the other reviewers commented that the book doesn't deal with the reality of IT workloads and scarcity of budget & resources many IT practitioners face today. My opinion is that IT professionals probably have the greatest need for time management than most other professionals. Seems that there are always urgent fires to put out (at least at companies where I've worked). Even so, I still think that one can and should aim to follow the guidelines in the book, without shortcuts, using the various time management principles that are taught in management courses. We all have to learn to find the time to do those things that are extremely important even though they're not urgent. An ounce of prevention...

I found this book extremely useful as a reminder of all the important areas to be considered in applying a data strategy to my organization. Especially useful was the chapter on logical and physical data modeling along with the many checklists presented.

I recommend this book to anyone concerned about data strategy and the need to manage that most important of corporate assets.

I thoroughly enjoyed this book, both for its delineation of a myriad of different data strategies, and as a valuable resource to walk one through the deployment of these strategies.

I am definitely recommending this book to my peers!

If you are data management professional, you will find that this book is only surface deep. For example, there is a chapter on Data Quality. If you want to learn more about data quality, you should read Larry English's book Improving Data Warehouse and Business Information Quality. There is a chapter on metadata. Again, if you want to know more about metadata, get a book or a few books on metadata. Use the reference after each chapter to find out the books on the chapter topic.

If you find this book helpful, this indicates you are new to data management.

A good introductory data management book.