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Buyer’s Guide: Selecting the best business intelligence (BI) tools

Learn how to select the best business intelligence (BI) tools for your business. Get tips on gathering business requirements, comparing types of BI software and picking BI vendors.

Buyer's Guide: BI tools and softwareThe potential benefits of business intelligence (BI) software go straight to the heart of running a successful organization: better decision making and improved business processes, ideally leading to bottom-line improvements. But while BI is no longer a speculative technology, implementing a BI system that can get the right data to the right people at the right time isn’t easy. In this guide, readers will get advice on how to select the best BI tools for their business, learn about the primary purchasing criteria for BI products and find out how to avoid fatal BI project flaws.

Business Intelligence Buyer's Guide Table of Contents

Selecting the best business intelligence tools for your business
Buying business intelligence software: Top 11 considerations
Gartner: Enterprise BI strategy rarely a one-size-fits-all approach
Setting key performance indicators can boost BI software user adoption
Business intelligence tools: Don't be 'tool myopic'

Selecting the best business intelligence tools for your business
By William McKnight, Contributor

The benefits ofbusiness intelligence (BI) have been proven repeatedly. BI strikes at the heart of the charter of a business – bottom-line improvement. No longer speculative, BI provides tangible benefits to an enterprise’s revenue and expenses. BI is about getting the right data to the right people at the right time.

Historically, BI has meant whatever we do to data in our post-operational data warehouses. That is not entirely true anymore. BI is done everywhere – in our operational environments, such as ERP, supply chain and call center systems, as well as data warehouses and other post-operational analytical structures.

BI, of course, needs data to be viable, and sometimes that means setting up additional data stores with data in a prepared state for the access. Sometimes there is a data store where BI access is needed, and sometimes that store needs to be built. However, data access is the layer in the data architecture that BI addresses. If the plumbing is robust but the presentation layer is lacking, all is lost. This guide will look at business intelligence vendors and methods.

There is no best or one-size-fits-all tool on the market. Multiple BI tools will be trained on any viable data store over the course of time. It’s an evolutionary progression, and there is no method of data access that is necessarily a “first port of call” for BI. Perhaps no technology term has been as overused as BI, so it is essential to dive much deeper than the label and figure out which tools you really need in your organization.

Selecting the best BI tool should start with requirements-gathering from those accessing data. These “users” need a BI tool like a hole in the head. What they need is data access through the right mechanism (reports, alerts, visualization, interaction, etc.). Dust is collecting on unused BI tools (“shelfware”) the world over, while frustrated users live with what is “good enough.” The end result is that Microsoft Excel is the most common BI tool. This is problematic.

Ideally, the requirements-gathering process begins not with “what do you want to see?” but with “what are your business goals?” Together, the BI expert and the user can then explore the robust possibilities that today’s BI market offers.

Business requirements gathering
Other questions to be asked during the requirements-gathering phase for BI include:

  1.  What are your short-term and long-term success criteria?
  2. Where are you now, relative to that plan and your objectives?
  3. What is viewed as a success for you and your team?
  4. How is your business changing? How will it be different in five years?
  5. What do you see as your company’s strengths as well as its vulnerabilities/weaknesses?
  6. Which operations/processes do you want to improve within your area of responsibility?
  7. What are the critical business decisions you make and/or critical business questions you must answer in order to achieve your objectives?
  8. What information or insights do you need in order to address these critical business issues and questions?

During the requirements-gathering phase, give only cursory consideration to the data sources. Data source selection, or building new databases for BI, can best be determined once you have all the answers to the above questions. I also advise considering likely future requirements in the process, even if they are not well formulated. Sometimes, in order to define these requirements, you’ll have to reach out to an experienced outside party with multiple full-lifecycle views of BI in your industry.

Infrastructure check
In order to aid the selection process, the following information should be gathered on a project-by-project basis early in the process for each user grouping:

  • Volumes/architecture of the data being accessed.
  • Data volatility.
  • Type of application.
  • Integration needs with other systems.
  • Number of users and their locations and roles.
  • Access schedule.

There are dozens of products in the marketplace that provide access to data stores, many of which offer various types of analytic capability.

One tool can fit multiple uses, but there is no equivalent of an enterprise “Swiss army knife.” Therefore, it is essential that a company select and deploy a small number of tools with complementary designs and capabilities that together support the specific use and usage pattern of each class of users. Effective sites will have three to four tools (for a midsized organization) or five to 10 tools (at a large organization).

Just as important as having complementary tools is not having any tools that compete (i.e., with similar features and benefits). It is simply too costly to buy, learn, deploy and support such tools and to resolve conflicts among users when resources become constrained. Choose a few tools well in order to match explicit business needs without proliferating.

Categories of BI tools
The marketplace requires BI buyers to understand which tool best fits their needs. The terminology used is confusing, with ingeniously subtle variations on common themes used throughout because there aren't enough suitable descriptive words to go around.

The categories of BI tools include:

  1.  Reporting tools
  2.  Desktop/traditional BI
  3. Multidimensional tools
  4. Data mining
  5. Data visualization tools

There are multiple ways BI tools can provide access data, but it is important to understand the value that each category provides.

Reporting tools, often a first port, provide enterprise reporting and analysis functionality that can support complex needs. They provide users with multiple software components that allow data to be accessed based on their particular needs. Ad hoc query or drill-down, slice-and-dice forms of analysis are best with desktop/traditional BI tools.

Reporting tools produce the most varied forms in the easiest manner of all the tools, but their ability to interact with the reports is limited. Other tools, like desktop BI tools, provide greater interactivity with the data. Specific reporting needs that are too complex in content, design, sourcing or format could continue to be handled with a reporting tool.

Multidimensional access involves building a structure separate from the relational data store (a "cube") that is optimized for high performance of a specific set of queries around a few dimensions and metrics.

Data mining has long been a means to attain high business value from a warehouse. As the means of automating discovery to explore and identify new business insight, it stands alone as an access method. For all other forms of BI, you must understand ahead of time what you’re looking for. Algorithmic data mining, however, will make you aware of situations that may represent new market opportunities or business problems that have yet to surface.

Finally, data visualization tools provide a means of making sense of vast amounts of detailed information through plotting, charting and otherwise cutting through the volumes of data to make visual sense.

Tool selection
A single tool can provide elements of many categories, but more likely it is a suite of tools from a vendor that will meet all of your data access capabilities. An organization’s strategy for vendor management (i.e., one large vendor vs. several smaller ones) should provide a strong rationale for the ultimate selection.

BI tool selection is not an all-IT affair. Once the requirements have been gathered, the infrastructure needs checked, and the tool categories matched to the requirements, users should be involved in the process in order to aid adoption and acceptance of the tools. Users can provide feedback on the look-and-feel elements of the selection. If the organization has made a decision about the data store upon which BI will be trained, then it might be effective to download and test time-limited trial versions of the BI tools that have made it to the final round of the selection process.

It is important to understand the business requirements before making a business intelligence purchase. Collecting a profile of the existing architecture that BI will be integrating with is another important criterion. The category of tool needed can then be determined and the tools short-listed and trialed inhouse, with users, in order to determine the best-fit BI tool to achieve the goal of the right data to the right people at the right time.

BI software and tools guideAbout the author:William McKnight is the president of McKnight Consulting Group. He works as a strategist, lead enterprise information architect and program manager for complex, high-volume, full-lifecycle technology implementations worldwide within the disciplines of data warehousing, master data management (MDM), business intelligence (BI), data quality and operational BI. Implementations by his teams, managed from both IT and consulting positions, have won IT best-practices awards. McKnight is a Southwest Entrepreneur of the Year award finalist and a frequent best-practices judge himself; in addition, he has authored more than 150 articles and white papers and given more than 150 keynote speeches and public seminars, both in the U.S. and abroad. McKnight holds an MBA and is a former VP of IT at a Fortune 50 company and a former DB2 engineer at IBM. He can be reached at

Business Intelligence Buyer's Guide Table of Contents

Selecting the best business intelligence tools for your business
Buying business intelligence software: Top 11 considerations
Gartner: Enterprise BI strategy rarely a one-size-fits-all approach
Setting key performance indicators can boost BI software user adoption
Business intelligence tools: Don't be 'tool myopic'


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