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This text aims to help you to maximize the potential of Business Intelligence in your organization. It includes stories of companies that implemented BI - those that have succeeded and those that have failed.
- Sales Rank: #3803862 in Books
- Published on: 2003-06-14
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .80" w x 6.90" l, 1.02 pounds
- Binding: Paperback
- 240 pages
From the Back Cover
Making business intelligence work: Start-to-finish guidance for managers
This book offers a true enterprise view of business intelligence. IBM expert Mike Biere shows managers how to create a coherent BI plan that reflects the needs of users throughout the organization-and then implement that plan successfully. Biere explains how to objectively assess the business case for BI, and identifies proven solutions for the obstacles that lead many BI projects to fail. Coverage includes:
- Setting appropriate expectations and goals for your BI project
- Understanding how the key components of a complete BI solution fit together
- Designing effective BI solutions-including content management, handling unstructured data, and end-user segmentation
- Providing effective support for BI end users
- Introducing Corporate Performance Management (CPM): an executive's view of BI
- Previewing tomorrow's "next wave" in BI solutions
- Comprehensive checklists for planning your BI project
About the Author
MIKE BIERE is Worldwide Sales Specialist for Business Intelligence Analytics Tools for IBM Corporation. He has more than 20 years' experience in business intelligence-related technologies, working in every stage of the BI project lifecycle, and in every role from sales and marketing to product development and technical support.
Excerpt. © Reprinted by permission. All rights reserved.
Preface
Let me begin by stating that this book is not intended to be used as a technical reference for your validation or argument in the evaluation or assessment of Business Intelligence solutions. I have avoided the use of products and acronyms whenever possible. This is not because I do not know the products or because I don't have an opinion about them. It is because I want you to think about what you are doing for Business Intelligence and why.
A "best-of-breed" BI tool can be implemented so poorly that it provides no value at all. A dated but well employed BI tool may bring spectacular business results. I probably will repeat myself a bit, including using the phrase "Activity does not equate to success." BI success does not lie in the volume of usage nor the volume of paper generated. BI success is measured in business impact and by the improvements in critical areas that can be attributed to its implementation.
I began working in the end-user computing arena in 1981 and have worked with nearly every tool and database on the market since then. Behind all these efforts lies a common theme--the need to produce key business information from existing data.
I do not pass judgment on any specific solution or vendor. I do, however, believe that too many organizations take the easy way out by selecting some tools, hoping the end users will "magically" emerge with what they want. Meanwhile, the rest of the "important" work in data processing goes on...and on...and on. If an organization decides to provide some data and analytics tools to end users to get them off the Information Technology (IT) Department's back, it will fail and the organization will end up spending much more in the long run because ultimately they'll have to attempt to get it right.
Your view and definition of BI will dramatically vary from others depending upon your role within the enterprise. If your position requires you to work with getting the corporate data into shape for BI, the issues you face will be drastically different than those of individuals trying to use what you have created.
If you are a non-technical end user, your definition probably will be filled with noble business initiatives and some usage and functional assumptions about the tools you will use.
An enterprise view of BI would combine definitions from all users and roles into a singular view with goals that span the enterprise--oops, I just gave away the rest of the material in this book. Please do not stop here.
Years ago, I was sitting in an introductory class to a new, exciting query and analysis tool. The instructor had been constantly hammering into us that the tool we were trying to learn was "intuitively obvious to use." One of my fellow students finally said, "I am sorry, but I don't seem to be getting it. I thought you said this was going to be intuitive!?" The instructor said, "Well, the more you use it, the more intuitive it becomes!"
We have all heard the adage that a million apes with a million typewriters given a million years would eventually write War and Peace. Sometimes, a BI solution can seem that way. If the users have to constantly flail at data with obtuse options in an attempt to produce a result, then something is dramatically wrong.
Business Intelligence solutions are anything but intuitive. Regardless of how many names and technologies have been applied to the discipline we now call BI, it is a difficult yet incredibly rewarding area in which to work. BI can change the course of how an enterprise operates and can keep an organization afloat in difficult times. BI elements can be used to discover trends and information that "normal" thinking would not have disclosed.
How does one get from "flailing" to spectacular success? Needless to say, your business has to be viable and in a position to increase profitability and implement changes. The heart of any BI success story begins with the corporate "intent" in implementing BI. Sometimes, a firm just gets lucky and discovers that increasing the level of information flow has a positive effect on the business. In most cases, many end users feel warmer and fuzzier because they are getting more information but could not begin to tell you whether it has changed the bottom line.
Business Intelligence is mostly query and reporting. In Chapter 2, I will apply a more formal definition of BI, but for now I will limit my definition to query and reporting. Of course, you may be asking, "Isn't there much more involved in today's BI solutions? What about data extraction, cleansing, and all the data preparation required?" Yes, there are many ancillary and necessary steps involved in delivering BI solutions. But at the heart of every solution is the need to access the data we've captured and to perform some analysis that we will use in our business.
Let's look at an Executive Information System (EIS). There is so much talk about "executive dashboards" today. Somewhere beneath the clever graphical interface and presentation lies some data and a corresponding set of values that were produced with a query tool. The trappings of the presentation style do not negate the need for a core technology to deliver the data.
The marketplace today is flooded with BI tools. There are numerous query and reporting solutions available, and most large organizations have installed several solutions that are being used for any number of business purposes. Are they all necessary? Are there significant, unique differences among them that justify having several "power tools" installed at once? The answers to these questions are usually "no" to the first and "maybe" to the second. Is there any harm in having sets of tools from different vendors? I submit that the answer to this question is a definitive "yes!"
The title of this book isBusiness Intelligence for the Enterprise. I have found that a very small number of organizations have attempted to establish a global view and effort in implementing BI. The majority of firms that practice BI tend to perform random acts of analysis on data.
The roots of BI date back to early mainframe query tools when data processing departments began to open corporate data stores to end users with 4GLs (fourth generation languages). These early BI implementations via 4GLs managed to excite the users as well as raise the frustration level on both sides.
IT was unhappy at the unexpected impact on existing systems, as well as the inevitable hand-holding required to get the tools working. IT also had to spend time it simply did not have trying to resolve many technical issues such as getting a tool to work properly in accessing a data source. The end users were unhappy because in every case there was far more work involved in extracting results from the data. There were far too many techno-geek aspects to getting the job done.
The worst impact was the rift between corporate IT and the end users. IT was perceived as keeping the keys to the castle and creating massive roadblocks to prevent the users from accessing their data. The end users were perceived as being technically inept and a bunch of "whiners" who always had to run to IT when the going got rough--which typically didn't take very long.
In every case, there were a few individuals who emerged as experts in the tools and usage. Some were from IT, and some were end users with a more technical aptitude. The number of individuals outside of IT that could actually do very much with an analytics tool was typically small. In many cases, these savvy end users went on to succeed at higher levels within the organization. Many of them are the drivers of point solutions today.
Let me present an example of an early BI implementer. Customer XYZ has a mainframe with lots of data stored in a variety of formats including VSAM, sequential datasets, and even tape that the users require for historical analysis. The data has been stored in efficient formats, such as packed-decimal to take up as little disk space as possible. Many of the text fields have intelligent keys where a couple of characters are used to describe longer information items (e.g., two positions in a longer field used to signify districts or other lengthy information).
This company has discovered a vendor tool that allows it to access and query this legacy information. However, setting up the access and performing actions, such as stripping out the intelligent key positions and translating them into understandable text, is not trivial. The vendor's suggestion is to extract the data in its raw form, transform the encoded values to understandable ones, and store the data in the vendor's proprietary format.
Even when the data has been molded into a source that is better for common business use, it is still not structured for the non-technical end users to do much with it. The processing requirements and calculations are more challenging than many end users can handle, so we now have an enriched set of data held in a proprietary source. However, the era of end users performing their own query and reporting functions began, and it has been in a state of continuous change ever since.
Today, there are more choices for analytics tools than years ago. Instead of having the data, the tools, and the analysis processes on the same platform (e.g., S/390), one can now remotely analyze a server from afar using tools on workstation platforms. Many corporations allow users to perform these analytics from a variety of tools with varying results.
The difference between traditional BI and BI at the enterprise level is significant. I am an avid fan of using fewer tools and centralizing BI at the server level. I use several keywords in discussing BI with customers. One of the first ones I toss out is math. BI is all about "the math."
BI users often want to perform very specific and difficult calculations. Regardless of the platform, the tool, or the technologies, few BI solutions allow users to drag some columns onto a report and select the Run option. Even the most elegant data warehouse structure assumes the users will need to perform some calculations beyond the basic storage structure of the data. Where and how one decides to perform the math can have an enormous impact on BI architecture
The other word I use in discussing enterprise level BI is awareness. Do different user departments, groups, and so on have effective intercommunication with each other such that they can share their BI efforts? In the overwhelming majority of cases, the answer is a ringing "no!"
Because BI efforts require data and math, does it not make sense that one would try to condense as much of the effort into as little iteration as possible? We probably have all heard about the scenario where different users walk into a meeting with different results supposedly based upon the same data. Do these events occur because they are using different tools or different data? What if they are using the same tools, but have different skill levels? What if all the results are incorrect?
The objectives for quality BI efforts are many. The guidelines I recommend in establishing a successful BI environment are scattered throughout this book. I have included a series of checklists in the Appendix at the end of the book, and I hope that they will assist in your selection of BI solutions. Now let's define this thing we dub Business Intelligence.
Most helpful customer reviews
14 of 14 people found the following review helpful.
For once -- a business book about technology and a MUST READ
By A Customer
......
If you:
- are tired of the increasingly unintelligible hype around corporate IT
- need to get your feet on the ground about how to apply IT for creating business value
- want to understand business intelligence for what it can really do for your organization (as opposed to what the product vendors tell you)
then read this book.
I've been in the software industry for twenty years, and this is one of those rare, honest books that speaks from long experience and with a welcome disregard for technical faddism and ivory tower theory.
This book is needed because the idea of "information at your fingertips" at most companies is still just that: only an idea. Instead, most organizations still operate inefficiently and clumsily from "islands" of information scattered about in everything from spreadsheets to CRM systems to mainframe COBOL programs whose authors have long since retired.
Even companies that have spents millions of dollars to correct this state of affairs have failed. Why?
This book is about making information available across the board, why you would want to, and how to give your technology of choice "traction" and an impact on the bottom line.
This is done from two perspectives: the technical and the human side.
The author is refreshingly frank in describing corporate IT disasters, and does an excellent job of exposing the human side of where they go wrong down in the trenches. Anyone who has been anywhere near an overbudget, underperforming, or ultimately worthless IT project (this should include most people in corporate IT by now) will read with a smile of recognition. Others should read before you spend: there is a lot of money and heartache to be saved. By demonstrating in everyday language that the hardest part to manage is human expectations, Biere performs a real service to the industry that is usually neglected, and gives managers, end users, and even vendors much insight on where to be proactive.
But this is not a collection of anecdotes. CIOs, CEOs, IT professionals, and beginners will gain a lot from the industry retrospectives, overviews of categories of tools, and the workbook approach for grasping the human side and the technical side at once. The author provides thinking and homework that MUST be done before even considering an expenditure, and asks the questions that even the most expensive consultants won't ask for you.
Because the author is with IBM, you might expect the book to promote IBM products. Not so. Mr. Biere manages to name almost no products, and yet covers the tools available comprehensively.
And college computer science professors: put this book in your curricula -- give your students a healthy dose of the "real world" before sending them out into it.
Well done, Biere.
9 of 10 people found the following review helpful.
A thoughtful and thought-provoking book about BI ...
By Richard Sawa
The tji-Boston reviewer is dead-on correct that this is a frank discussion about BI. Biere will help you to think about BI, and he will help you to think clearly.
Business Intelligence for the Enterprise is written for the customer. The author is a sales guy, who works for a vendor (IBM - Good Grief!), AND he has written a book for the customer. Why?
He is obviously interested in seeing Enterprise BI succeed.
This book will help you think through sales hype, and move closer to success. In a certain sense, it is a book written to help business people like you deal with sales people like Mike Biere. Ironic? Yes. And no.
A perspective like this doesn't come from being slick and clever (goodness knows there is an endless array of slick and clever sales people.) Rather, it comes from making a mature commitment to one's working life, which Biere has obviously done.
It is as important for the C-level IT professionals to read as it is for their C-level bosses and colleagues. Needless(?) to say it is also an important read for those who are going to do the actual work of implementing the BI strategy.
Read this book, but only if you are willing to spend some time thinking....
6 of 7 people found the following review helpful.
Good for managers, too generic to be used by DW developers
By Andrea Vincenzi
The author is an IBM veteran who spent more than 20 years in the sales and product support divisions, except for a short period in a company specialized in Data Warehousing, so he naturally puts in this book a lot of his experiences and he also describes the history of BI in terms of architectures and technologies.
I had the impression that the target audience is mainly made by managers involved in BI projects, on either sides (vendors, consulting companies, customers).
One obvious comment from an Italian like me is that, like with many other books written in the US, the average size of the projects described in this book is rather large compared to what we are used to, and could only be applied to a handful of companies here in Italy.
The best feature of the book is the large number of real life examples that it contains. This can be a real help for a manager of a company who doesn't know the risks connected with BI projects and wants to learn from the many (and sometimes very costly) errors made by other people and companies in similar situations.
Under this aspect the book contains a lot of common sense and is a good reading, but don't look in it for innovative contents or for clear explanations of key technologies, buzzwords and project methodologies.
In most cases the book is limited to describe different situations (usually problematic), and to give some advise, without really delving into technical details.
Often I saw the author asking himself several questions about the typical problems that are encountered in a BI project, but then I couldn't find the answers.
Although there are no references to specific products, in more than one occasion it seems that the fact that the author comes from IBM comes to the surface, like when he prefers the "single provider" approach versus the "best of breed" (Chap. 4), or when he talks about the qualities of the mainframe as opposed to distributed environments (chap 7).
In conclusion, is this book worth reading? I have to say that whenever I read a book about BI and Data Warehousing I can't avoid comparing it with the books from Mr Kimball, which I consider the absolute reference in the field. This might not be fair, but it makes sense, since our time is limited, to read only those books that add something new to what we already know.
In this case the answer is yes, but only for a specific target, i.e. managers of companies who are about to start their first BI project. The rest of the project team would probably find most of the information in this book not very useful.
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