- Tapa blanda: 384 páginas
- Editor: Addison-Wesley Educational Publishers Inc; Edición: 01 (15 de junio de 2005)
- Idioma: Inglés
- ISBN-10: 0321240995
- ISBN-13: 978-0321240996
- Valoración media de los clientes: Sé el primero en opinar sobre este producto
- Clasificación en los más vendidos de Amazon: nº592.692 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
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Data Strategy (Inglés) Tapa blanda – 15 jun 2005
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Without a data strategy, the people within an organization have no guidelines for making decisions that are absolutely crucial to the success of the IT organization and to the entire organization. The absence of a strategy gives a blank check to those who want to pursue their own agendas, including those who want to try new database management systems, new technologies (often unproven), and new tools. This type of environment provides no hope for success. Data Strategy should result in the development of systems with less risk, higher quality systems, and reusability of assets. This is key to keeping cost and maintenance down, thus running lean and mean. Data Strategy provides a CIO with a rationale to counter arguments for immature technology and data strategies that are inconsistent with existing strategies. This book uses case studies and best practices to give the reader the tools they need to create the best strategy for the organization.
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:
Identify the real risks and bottlenecks you face in delivering dataand the right solutions
Integrate enterprise data and improve its quality, so it can be used more widely and effectively
Systematically secure enterprise data and protect customer privacy
Model data more effectively and take full advantage of metadata
Choose the DBMS and data storage products that fit best into your overall plan
Smoothly accommodate new Business Intelligence (BI) and unstructured data applications
Improve the performance of your enterprise database applications
Revamp your organization to streamline day-to-day data management and reduce cost
Data Strategy is indispensable for everyone who needs to manage enterprise data more efficientlyfrom database architects to DBAs, technical staff to senior IT decision-makers.
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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...
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...
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.
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.