Do you think business intelligence is only for massive enterprises? In the past, that may have been the case, but new techniques are quickly driving business intelligence to small- and medium-sized businesses - with amazing effects. There's no longer any need to run your business on intuition when affordable, modular business intelligence systems can give you hard facts, help answer "what if" questions, and tie back into your business planning systems to help make implementation easier and more effective. In The Shortcut Guide to Achieving Business Intelligence in Midsize Companies, author Don Jones introduces you to the key concepts of business intelligence, including data modeling, data warehouses, OLAP, and more, and explains how the same techniques and technologies used by the "big boys" are now available to small- and medium-sized businesses who don't want, or can't afford, multi-month implementations that require hordes of specialized consultants.
For a few years now, business intelligence have been buzzwords of the IT industry. Unlike a lot of IT buzzwords-like "Web 2.0"-business intelligence actually carries some weight, has a definite meaning, and brings real value to businesses. Business intelligence-or BI, as insiders like to call it-refers to the practice of helping a business acquire a better understanding of itself. More broadly, BI also refers to the skills, technologies, applications, and practices involved in bringing that understanding to light.
The term business intelligence was first used in a 1958 article by IBM researcher Hans Peter Luhn, who defined it as the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal. In other words, BI isn't just about technology-centric concepts such as data warehousing or business analytics; BI is really about understanding the relationships between different aspects of your company so that you can guide the company toward specific goals, like increasing market share and improving customer satisfaction.
The IT industry-being technology-centric, of course-uses the term BI as a sort of umbrella phrase that covers all the technologies and capabilities used to gather facts about the business, present those facts in a way that makes relationships clearer, and allow manipulation of those facts to project "what if" scenarios-all intended to help guide better decision making.
The driving force behind business intelligence is that companies are drowning in unrelated facts that come from silos: payroll data, financial data, customer data, vendor data, and so on. BI pulls all that data together and correlates it. The data may seem unrelated, but in fact everything in the business is related somehow-if some data is truly unrelated, then why is it in the business in the first place? BI doesn't generate new data-it simply makes it easier to explore overlooked relationships between data.
Chapter 1 of The Shortcut Guide to Achieving Business Intelligence in Midsize Companies takes you through the goals of BI, provides a brief technical overview of the concepts, components, and visualizations of BI, and finally discusses the use of BI for analysis and decision-making.
How, exactly, do you "get" a business intelligence (BI) system into your organization? BI hasn't traditionally been something you just install onto a server or client computer, so it's important to understand the process, tools, and techniques that are involved in implementing and creating it. Some of these may, in fact, be major reasons why your midsize company has avoided BI in the past-making it even more important to understand not only the technologies, tools, and techniques but also how they've evolved in recent years to meet the needs of companies other than giant enterprises.
In this chapter, I'll explain the basic processes by which BI is introduced into an environment. I''ll also look at some of the reasons BI is traditionally a time-consuming and expensive proposition for most companies, and set up some of the ways in which you can implement BI more easily and for less money. Think of this chapter as the "BI life cycle"-a look into what BI actually looks like inside an organization like yours.
Assembling Your Business Data
BI is, first and foremost, all about data. The ultimate purpose of BI is to bring together data from many different sources so that you can start making connections, finding patterns, and spotting trends that wouldn't be apparent otherwise. That means the first step in implementing BI is deciding what business data you'll need to assemble, and figuring out how to get it all into one place. The actual technologies for doing so are less important right now; we're concerned with the different kinds of data that drive your business and the ways in which that data is currently stored and used. That information will help us decide which techniques you should use to pull that data into a BI platform.
There is definitely a pervasive belief that midsize companies simply can't afford, can't handle, or can't appreciate business intelligence (BI). I even run into executives at midsize companies who absolutely believe that companies the size of theirs don't need BI and can't benefit from it. It simply isn't true, and in this chapter, I'm going to play "Mythbusters" and address the most common misinformation regarding BI as it relates to these companies.
Before I do so, however, I want to get one of the most harmful pieces of misinformation out of the way, which is this: Midsize companies can't benefit from BI. That's patently false; it's like saying that midsize companies can't benefit from customer relationship management (CRM), accounting software, payroll software, or any other common business tool. Although it's true that many of these technology solutions began in extremely large companies, the fact is that any company can run itself more effectively and efficiently when these tools are available. It's also true that the CRM solutions (to take one tool as an example) used by giant enterprises are built differently than those used by midsize companies, but that doesn't mean midsize companies don't benefit from their particular versions.
In fact, that's one of the common themes you'll find in this chapter: Midsize companies can and do benefit from the same business tools and capabilities as giant enterprises; those tools are simply built specifically for the midsize market, and are often easier, less expensive, and faster to adopt and use than the ones designed for giant enterprises. On to the myths.
At this point, you should be at least ready to consider a business intelligence (BI) solution for your midsize company - and you may even be outright convinced that it's the right tool for your business. So how do you get into business intelligence and add a BI solution without disrupting your company? Without breaking the bank? Without having to add staff members with specialties you've never even heard of before? My goal in this chapter is to help answer exactly those questions, with practical advice for bringing BI into your midsize company.
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