Since the early 90's, BI applications have evolved dramatically in many directions, due to the exponential growth of information. The purpose of this document is to give an overview, and above all updated, of everything that Business Intelligence involves within organizations and their way of evolving over time. Business Intelligence (BI) applications are decision support tools that allow real-time, interactive access, analysis and manipulation of critical information for the company.
1. Introduction.
Historically, Business Intelligence technology has found place at two primary levels: among senior executives who need to obtain strategic information, and among line-of-business managers who are responsible for tactical analysis. These traditional decision support activities are important, but they only superficially show the potential of business intelligence within the company, involving perhaps 5% of users and 10% of available data (Information Builders, 2005).
Since the early 1990s, BI applications have evolved dramatically in many directions, due to the exponential growth of information. From mainframe-generated operational reports, statistical modeling of advertising campaigns, multidimensional OLAP environments for analysts as well as dashboards and scorecards for executives. Companies are beginning to demand more ways to analyze and report data.
Investments in business applications, such as resource planning (ERP) and customer relationship management (CRM), have resulted in huge amounts of data within organizations. These organizations now want to leverage these investments and use the information to help them make better decisions, be more agile with organization, and have a better understanding of how to run their businesses.
For them, many small and medium-sized companies are adopting BI to help them start their businesses.
The heart of Business Intelligence is the ability of an organization to access and analyze information, and then exploit its competitive advantage. In the digital age, the capabilities that Business Intelligence offers will be the difference between success and failure.
2. Brief history of BI
Organizations once relied on their information systems departments to provide them with standard and customized reports. This occurred in the days of mainframes and minicomputers, when most users did not have direct access to computers. However, this started to change in the 70's when server-based systems became the fashion,
Still these systems were primarily used for business transactions and their reporting capabilities were limited to a predefined number of them. The information systems were overloaded and users had to wait for days or weeks to obtain their reports in case they required reports other than the available standards.
Over time, executive information systems (EIS) were developed, which were adapted to support the needs of executives and managers. With the entry of the PC, and networked computers, BI tools provided users of the technology to create their own basic routines and personalized reports.
Figure 1 shows a brief historical overview of how what is now known as Business Intelligence developed, it can also be seen how the applications related to decision support have evolved over time.
Figure 1. Life cycle of decision support applications
Source: Business Intelligence Road Map (Moss & Atre, 2003)
3. Definition of Business intelligence
Business Intelligence (BI) applications are decision support tools that allow real-time, interactive access, analysis and manipulation of critical information for the company. These applications provide users with a greater understanding that enables them to identify business opportunities and problems. Users are able to access and leverage a vast amount of information and analyze their relationships and understand the trends that are lately supporting business decisions. These tools prevent a potential loss of knowledge within the company that results from a massive accumulation of information that is not easy to read or use. (CherryTree & Co., 2000)
4. Importance of BI in organizations
Too much information is not power, but knowledge is. Too often, transforming and analyzing all of the information and data that companies themselves generate becomes a real problem, and therefore decision making becomes desperately slow.
BI technologies try to help people understand data more quickly so that they can make better and faster decisions and ultimately improve their movements toward achieving business goals. The key drivers behind BI goals are to increase organizational efficiency and effectiveness. Some of the BI technologies aim to create a faster and more accessible flow of data within the organization. On the other hand, novel BI technologies take a more aggressive approach by redefining existing processes with new, much more streamlined ones that eliminate large numbers of steps or create new capabilities.
In a recent survey by Gartner, BI was ranked No. 2 on the CIO's list of technology priorities for 2005, after ranking No. 2 in 2004.
Due to this new emphasis on BI, the market for BI software tools around the world grew 7.7% in 2004, based on preliminary estimates of the composite market.
Growth in 2004 was driven by high performance from specific vendors, including Cognos and Microsoft. The ranking did not change with respect to 2003 as expected. The top three BI tool vendors in the global market, according to Gartner data, are:
| Provider | Position in the shared market |
| Business Objects | one |
| SAS Institute | two |
| Cognos | 3 |
Table 1. Largest BI tool providers
Source: Gartner Dataquest (February 2005)
5. Types of BI products
BI software tools are used to access business data and provide reports, analysis, visualizations and alerts to users. The vast majority of BI tools are used by end users to access, analyze, and report against the data that most frequently resides in data warehouses, data marts, and operational data warehouses. Application developers use BI platforms to develop and deploy applications (which are not considered BI tools). Examples of a BI application are budgeting and financial consolidation applications.
Currently the BI tools market is made up of two subsegments: Enterprise BI suites (EBIS) and BI platforms. Most of the BI tools, such as those developed by the vendors mentioned in Table 1, are Enterprise BI and BI platforms.
Gartner Dataquest (2005) made a five-year forecast, based on a preliminary estimate of market size and a review of inhibitors and drivers, concluding that the total BI tools market projects growth of $ 2.5 billion in 2004 to $ 2.9 billion in 2009, with an annual growth rate of 7.4%.
6. Contrasts: Business BI vs. Platforms
Tiedrich (2003) mentions that BI platforms are application development environments, they commonly offer a coding language like Visual Basic and other languages for creating custom applications. Also in his
| Advantage. | Disadvantages |
| Custom applications. | Complexity in application development |
| High analytical functionality. |
Table 2. Advantages and disadvantages of BI platforms
Source: Gartner Dataquest (June, 2003)
BI platforms are used when there is a need to analyze complex applications with many calculations (for example, profitability of a product) or to create friendly applications for occasional users.
Instead the business BI tools contain standard functionality. Once one or more data sources are mapped by the Enterprise BI Suite (EBIS) tools, the functionality comes to life. Although some tools contain some coding facilities, creating custom applications is a challenge.
As told by Tiedrich (2003), a consultant to Gartner, EBIS contains the following advantages and disadvantages.
| Advantage. | Disadvantages |
| Simpler implementation. | Less analytical functionality |
| Standard functionality. | Little ease of customization |
Table 3. Advantages and disadvantages of Business Intelligence Business
Source: Gartner Dataquest (June, 2003)
EBIS are usually used when there are many users of various levels of technical skill, each with less analytical reporting and view requirements (eg, administrative reporting or simple variant analysis).
7. BI technologies
During the training period, companies have actively discovered new ways to use their data to support decision-making, optimize processes, and perform operational reporting. And during this era of inventions, BI technology vendors have built software niches to implement every new pattern of applications that companies invent. These application patterns result in software products focused exclusively on five BI styles (Microstrategy, 2002), such as:
- Business report. Written reports are used to generate highly formatted static reports intended to expand your distribution with many people. Analysis cubes. Cubes based on BI tools are used to provide analytical capabilities to business managers. Ad Hoc Query views and analytics. Relational OLAP tools are used to allow experts to view the database and view any response and convert it to low-level transactional information. Data mining and statistical analysis. They are tools used to perform predictive modeling or to discover the cause-effect relationship between two metrics. Delivery of reports and alerts. Report distribution engines are used to send complete reports or notices to a large number of users,These reports are based on subscriptions, calendars, etc.
Up to this point, large companies have had to buy different sets of BI tools from different vendors, with each tool targeting a new BI application and each one giving the user functionality in just one of the BI styles.
One way to view these BI styles is to create a two-dimensional space (Figure 2) where the vertical axis represents the sophistication and interactivity of the analytical process and the horizontal axis represents the scale, or size, of the user population. This is when the 5 BI styles can be located within the quadrant.
Figure 2. The five styles of Business Intelligence
Source: Microstrategy, 2002
The following table shows the technologies that are used for Business Intelligence and which fall within the five styles mentioned above.
| BI technologies |
| Relational database servers. |
| OLAP database servers |
| Data Warehouses |
| Data Marts |
| Data transformation and cleaning tools |
| Report and view tools |
| Analysis and exploration tools |
| Data visualization tools |
| Data Mining tools |
| Scorecards, portals, and dashboards |
| Spreadsheets |
| Prediction and modeling tools |
| Alert and notification systems |
| Analytical applications |
Table 4. Technologies used in Business Intelligence
Source: Lokken (2001)
8. Operational BI
To keep pace with competition, companies increasingly demand Business Intelligence at the operational level, embedded analysis within processes to handle exceptions and make decisions in real time.
Some corporate users who are implementing techniques such as tools from vendors such as SAS Institute Inc., Information Builders Inc. and Cognos Inc.
Source: Information Builders (Consulted in June 2005)
9. Critical success factors.
Lokken (2001) mentions that all BI systems have a critical number of success factors in common, since they:
- They provide access to adequate data. Without organizing the data, it is difficult to achieve. They increase the ability of users to understand the results. Saturating people with numbers these days creates more problems than they solve. Ten years ago the problem was getting the data; But today it has more to do with managing them. They increase the understanding of business by users. Knowing what the data says is a good thing, but today you need to know what to do with it. This knowledge is difficult to build within a piece of software. They help communicate the findings and take action. It is rare that an individual can execute anything significant within an organization without involving others.
The five critical business success factors to consider when choosing an EBIS are:
- Minimize total costs of ownership. Target high ROI opportunities. Leverage existing data architecture. Meet end-user requirements. Ensure maximum scalability and performance.
Today, BI must address these five aspects and help simplify the entire sea of data for users. So BI success is never an accident; when companies reach it they achieve the following benefits:
- They make better decisions with amazing speed and confidence. They streamline their operations. They reduce the life cycles of their products. They maximize the value of product lines and anticipate new opportunities. Do a better and more focused marketing improving relations with customers and suppliers by equal.
However, organizations must correctly understand and address 10 critical challenges for BI success (Atre, 2003). BI projects fail because:
- Companies fail to recognize that BI projects are inter-organizational business initiatives, and to understand such initiatives differ from typical independent solutions. There is a lack of commitment on the part of sponsors (who have authority in the company. There is little Availability of business representatives. There is no available and skilled staff. There is a bad concept of BI software. They do not work under a detailed structure. There is no business analysis or standardization. There is no appreciation of the impact caused by data from Poor quality in business profitability. The need to use metadata is not understood. Too much trust in non-aligned methods and tools.
10. BI risks
Suffice to say, the proper use of BI tools can make the difference between life and death for many companies, between stagnation and growth, between opaque results and outstanding financial performance, between impersonal and poor service. quality and excellent personalized customer service, and between the optimal relationship with suppliers and the loss of the benefits of working with them and with other business partners. For all this BI is important. (Tiedrich, 2003)
As a risk, the risk involved is not too much properly speaking to assess the real needs of BI in the company and then select the most appropriate supplier and its products, as well as their implementation.
The biggest technological risk is that technology is changing rapidly. Naturally, new technologies carry some risk until they are fully tested. For example, the use of mobile technology for BI has been adopted very slowly.
Two of the most important risks are the ability of sellers to comply and ultimately, their viability, which is something to consider.
Some of the big risks associated with using BI tools are data-driven. The data that is used is not transformed properly. Because companies often choose their own BI tools in a business environment, a company may end up with multiple tools, as well as multiple data marts with data that is not clearly defined or meta data that is not compatible. This can lead to different conclusions about the same data.
11. Magic Quadrants of Business Intelligence
A magic quadrant was an analytical tool created and promoted by the Gartner company and which shows a graphic representation of the shared market in a certain period of time. Gartner Magic Quadrants provide companies with a means to identify and differentiate service providers in the information technology sector.
As Gartner defines, leaders in the magic quadrants are those software manufacturers that operate well today, have a clear vision of market direction, and actively develop the skills necessary to maintain their market leadership position.
Below are the 2 magic quadrants provided by Gartner dated November 2004. The first one is for Business Intelligence platforms and second for Business intelligence suites.
Figure 4. Magic Quadrant of BI Platforms
Source: Gartner Research (November 2004)
Figure 5. Magic Quadrant of BI suites
Source: Gartner Research (November 2004)
The way of interpreting it according to the specialists is as follows: those listed in the main quadrant can offer a great service to practically any client. Others could be companies that supply niche markets, so the notes deal with the niches of each of the companies and describe the 'favorable points' of all of them.
In this case, we are talking mainly about large corporate clients. A Magic Quadrant is still potentially useful for small and medium-sized enterprises (SMEs), but they may have to calibrate additional aspects such as 'how that particular vendor would contact me.' "
The Magic Quadrant should be taken as a tool and not as a specific guide to action. In the case of Business Intelligence, the great visionary until November 2004 is COGNOS. (Gartner, 2004)
For Gartner, visionary companies are those that present a clear focus on market direction and guide their efforts in this regard, and that can still optimize their services. The consultancy defines CPM as the methodologies, metrics, processes and systems used to monitor and manage the performance of a company.
Aligning execution with corporate strategy, Cognos CPM solutions are built on: the strength of the Cognos Enterprise BI Series, the industry's most comprehensive Business Intelligence tool - your budgeting platform, the Cognos Enterprise Planning Series, modeling and forecasts; and Cognos Metrics Manager, the most robust and flexible dashboard solution on the market. (Cognos, 2005)
12. Hype cycle of Business intelligence (Gartner, 2004)
This cycle was also defined by Gartner to model the introduction and development of new technologies.
The Hype Cycle is a graph that measures the various technologies according to a life cycle. Its stages are the "technological trigger" (when the concept appears on the market), "the peak of inflated expectation" (when much is said about the concept, but it is little applied), "the valley of disappointment" (when the tool it is below what was expected of her), "the slope of tolerance" (the path to maturity) and the "productivity plateau" (when it reaches maturity).
Since Gartner published the first BI Hype Cycle in December 2001, some changes have occurred
ERP-based BI descended into the valley of disappointment. However, it is likely to rise to the plateau of productivity. Analytical CRM (aCRM) keeps its place and its vendors are moving their attention to other areas. Corporate Performance Management (CPM), which emerged in the past year, is rapidly climbing to the peak of inflated expectations. Due to its high impact on administrative processes, mass adoption is likely to be a relatively slow process. Business Activity Monitoring (BAM) is another trend that is rapidly escalating towards the peak of inflated expectations. BI platforms, EBIS (Enterprise BI Suite), OLAP and production reports remain stable.
BI's Hype Cycle clearly shows that technological innovation precedes applications. BI mobile can re-emerge as something completely different. The same can happen with BI Web Services, XML-based BI Distribution, and collaborative BI.
Figure 6. Hype cycle of business BI
Source: Gartner Research (November 2004)
13. Conclusions
Organizations must use BI to leverage investments made in previous years in business applications that have resulted in the use of huge amounts of data; In this way, BI validates, measures and manages new opportunities and investments in new businesses.
Business Intelligence positions a company to generate the highest value from existing business lines and anticipate new opportunities. In addition, Business intelligence systems can help the company reduce product development cycles, streamline operations, fine-tune marketing campaigns, and improve relationships with customers and suppliers, all of which mean lower costs and higher profit margins.
With Business Intelligence, the company can analyze trends that represent important new opportunities and anticipate potential problems and make adjustments before they become a problem.
In the digital age, the capabilities that Business Intelligence offers will be the difference between success and failure.
References
- Atre, S. (2003), “The top 10 critical challenges for business Intelligence success”, ComputerWorld, Vol.37. No. 23. www.computerworld.com/services/ whitepapers / story / 0,4793,82630,00.html (accessed June 2005).Buytendijk, F., Dresner, HJ, Linden, A., Tiedrich A., Hostmann B., Herschel, G., Gassman, B. (2004). Hype Cycle for Business Intelligence, 2004, Gartner Cognos (2005), Cognos positioned as leader in Gartner's latest study on the Business Intelligence market, http://www.cognos.com/en/pressfolder/2004/2712.html (Consulted in June 2005) CherryTree & Co. (2000), Business Intelligence-The Missing Link, CherryTree & Co.Dresner, HJ, Hostmann B., Buytendijk F. (November, 2004), Magic Quadrants for Enterprise BI Suites and Platforms, Gartner Dresner HJ, Buytendijk F., Friedman T. (November, 2003),Predicts 2004: Business Intelligence Markets, Gartner Friedman, T. (2004). Management Update: The Cornerstones of Business Intelligence Excellence. Gartner Graham, C. (March, 2005), BI Software Becoming a Top Priority for CIOs, Gartner Havenstein, H. (2005). Users turn to operational business intelligence tools: Emerging capability promises real-time access to most data, http://www.computerworld.com/databasetopics/businessintelligence/story/0,10801,100506.00.html?SKC=businessintelligence-100506 (Consulted in June 2005)Emerging capability promises real-time access to most data, http://www.computerworld.com/databasetopics/businessintelligence/story/0,10801,100506.00.html?SKC=businessintelligence-100506 (Consulted June 2005)Emerging capability promises real-time access to most data, http://www.computerworld.com/databasetopics/businessintelligence/story/0,10801,100506.00.html?SKC=businessintelligence-100506 (Consulted June 2005)
INFOchannel México, (2005), The boom of BI, INFOchannel México, http://0-site.securities.com.millenium.itesm.mx/doc.html?pc=MX&doc_id=70767142&query=business%3ABusiness%3AIntelligence&hlc=es, (Consulted in May 2005) InformationBuilders (2004), Business Intelligence Goes Operational: On the Front Lines Making a Bottom-Line Difference, http://www.informationbuilders.com/solutions/operational_bi.html (Consulted in May 2005) Laudon, Kenneth C.; Laudon, Jane P. (2004) Management Information Systems. Editorial Pearson Prentice Hall, New Jersey USALokken, B. (2001), Business Intelligence: An Intelligent Move or Not ?, http://bi.ittoolbox.com/browse.asp?c=BIPeerPublishing&r=%2Fpub%2FAO031202%2Epdf, (Consulted in May 2005) Microstrategy (2004). The 5 Styles of Business Intelligence: industrial-strength business intelligence,whitepaper.informationweek.com/cmpinformationweek/ search / viewabstract / 64521 / index.jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial. Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005) Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted in May 2005).informationweek.com/cmpinformationweek/ search / viewabstract / 64521 / index.jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison- Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005) Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Accessed May 2005).informationweek.com/cmpinformationweek/ search / viewabstract / 64521 / index.jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison- Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005) Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Accessed May 2005).com / cmpinformationweek / search / viewabstract / 64521 / index.jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005) Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted in May 2005).com / cmpinformationweek / search / viewabstract / 64521 / index.jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005) Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted in May 2005).jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com /whitepaper/WID537.pdf, (Consulted in May 2005).jsp (Consulted in June 2005) Moss, LT, Atre, S. (2003).Business Intelligence Roadmap: The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products/ whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com /whitepaper/WID537.pdf, (Consulted in May 2005).The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products / whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted in May 2005).The Complete project Lifecycle for decision support applications, Editorial.Addison-Wesley, USA Quinn, K. (2003), Establishing a Culture of Measurement: A Practical Guide to BI, informationbuilders, www.informationbuilders.com/cgi-shell/products / whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted in May 2005).com / cgi-shell / products / whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted May 2005).com / cgi-shell / products / whitepaper / whitepaper_form.pl? Whitepaper_Code = WHTBI_PhilosophyTiedrich Alan (June, 2003), Business Intelligence Tools: perspective, Gartner, (Consulted in May 2005).Timo E., Rowland, S., Byrne, K., Surak B., (2003), Implementing a Business Intelligence Strategy: A Practical Guide to Business Intelligence Standardization, Bussines Objects, www.dmreview.com/whitepaper/WID537.pdf, (Consulted May 2005).(Consulted in May 2005).(Consulted in May 2005).
