BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.
Business intelligence applications can be:
Introduction
Microsoft® SQL Server™ 2005 is a complete business intelligence (BI) platform that provides the features, tools, and functionality to build both classic and innovative kinds of analytical applications. This paper provides an introduction to the tools that you will use to build an analytical application, and highlights new functionality that makes it easier than ever to build and manage complex BI systems.
The SQL Server 2005 Business Intelligence toolset delivers end-to-end BI application integration,
Design:
Business Intelligence Development Studio is the first integrated development environment designed for the business intelligence system developer. Built on Visual Studio® 2005, the Business Intelligence Development Studio delivers a rich, integrated, professional development platform for BI system developers. Debugging, source control, and script and code development are available for all components of the BI application.
Integrate:
Integration Services has been rewritten to perform complex data integration, transformation, and synthesis at high speed for very large data volumes. The Business Intelligence Development Studio makes building and debugging packages positively fun. Integration Services, Analysis Services, and Reporting Services work together to present a seamless view of data from heterogeneous sources.
Store:
SQL Server 2005 blurs the lines between relational and multidimensional databases. You can store data in the relational database, in the multidimensional database, or use the new Proactive Cache feature to get the best of both worlds.
Analyze:
Data Mining in SQL Server has always been easy to use. Now it's even better with the addition of important new algorithms, including Association Rules, Time Series, Regression Trees, Sequence Clustering, Neural Nets, and Naïve Bayes. Important new analytical capabilities have been added to Analysis Services cubes as well: Key Performance Indicator framework, MDX scripts, and other built-in advanced business analytics. The Reporting Services report delivery and management framework enables easy distribution of complex analytics to the widest possible audience.
Report:
Reporting Services extends the Microsoft Business Intelligence platform to reach the business user who needs to consume the analysis. Reporting Services is an enterprise managed reporting environment, embedded and managed using web services. Reports can be personalized and delivered in a variety of formats and with a range of interactivity and printing options. Complex analyses can reach a broad audience through the distribution of reports as a data source for downstream business intelligence. New in SQL Server 2005 is Report Builder. Report Builder provides for self service ad hoc reporting by the end user. Ad hoc query and analysis tools from Microsoft and their partners will continue to be a popular choice for accessing data in Analysis Services and relational databases.
Manage:
The SQL Server Management Studio integrates the management of all SQL Server 2005 components. Through Management Studio, BI platform components gain enhanced scalability, reliability, availability, and programmability. These enhancements provide significant benefits to the business intelligence practitioner.
The following table presents an overview of the components of a business intelligence system, and the corresponding Microsoft SQL Server 2000 and SQL Server 2005 components.
| Component | SQL Server 2000 | SQL Server 2005 |
| Extract, transformation, and load | Data Transformation Services (DTS) | SQL Server 2005 Integration Services |
| Relational data warehouse | SQL Server 2000 relational database | SQL Server 2005 relational database |
| Multidimensional database | SQL Server 2000 Analysis Services | SQL Server 2005 Analysis Services |
| Data mining | SQL Server 2000 Analysis Services | SQL Server 2005 Analysis Services |
| Managed reporting | SQL Server 2000 Reporting Services | SQL Server 2005 Reporting Services |
| Ad hoc reporting | | SQL Server 2005 Reporting Services |
| Ad hoc query and analysis | Microsoft Office products (Excel, Office Web Components, Data Analyzer, SharePoint Portal) | Microsoft Office products (Excel, Office Web Components, Data Analyzer, SharePoint Portal) |
| Database development tools | SQL Server 2000 Enterprise Manager, Analysis Manager, Query Analyzer, various other | SQL Server 2005 Business Intelligence Development Studio (New!) |
| Database management tools | Enterprise Manager, Analysis Manager | SQL Server 2005 SQL Server Management Studio (New!) |
Two components are new for SQL Server 2005: SQL Server Management Studio and SQL Server Business Intelligence Development Studio. The other primary BI components – Integration Services, Analysis Services OLAP, Analysis Services Data Mining, and Reporting Services – are substantially different and improved in SQL Server 2005. The SQL Server 2005 relational database contains several significant new features. Although the Microsoft Office query and portal tools are not part of SQL Server, the current releases will continue to work with SQL Server 2005. The BI functionality in Microsoft Office will evolve with the Office product release cycle.
BI systems beneficiaries include a wider and wider group of users starting from specialists in controlling, financial reporting and finance, through salespeople, up to members of the board. Sectors that use BI systems most frequently include trading companies, insurance companies, banks and a financial sector, telecommunications and manufacturing companies,
Retail industry
Insurance
Banking, finance and securities
Telecommunications
Manufacturing industry
We live in the information economy. Knowledge is the power. Information is the lifeblood of companies. It’s clear that this idea contains a lot of truth. Smart use of information and information technology can be one of the most effective ways to gain a competitive advantage and thrive in times of change with dynamic business environment. Also most of the executives find that they and others in their organizations fall far short of where they ought to be with regard to having optimal capabilities for processing the information.
Most companies collect a large amount of data from their business operations. To keep track of that information, a business and would need to use a wide range of software programs , such as Excel, Access and different database applications for various departments throughout their organization. Using multiple software programs makes it difficult to retrieve information in a timely manner and to perform analysis of the data.
The term Business Intelligence (BI) represents the tools and systems that play a key role in the strategic planning process of the corporation. These systems allow a company to gather, store, access and analyze corporate data to aid in decision-making. Generally these systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few.
Efforts undertaken to develop BI systems have resulted in many business solutions that allow for effective support of manager’s work. Practice shows that the most significant business effects are obtained while using the following analyzes offered by the BI systems,
A study conducted by market research firm Dynamic Markets has yesterday revealed that business intelligence systems are failing to improve operational performance or impact decision making within US and UK businesses. A study conducted by market research firm Dynamic Markets has yesterday revealed that business intelligence systems are failing to improve operational performance or impact decision making within US and UK businesses. The research, based on interviews with 218 operational executives and front line management and conducted between November 2006 and August 2007, provides a snapshot of current use and satisfaction with Business intelligence systems and their impact on operational performance.
Although many organizations have adopted BI tools in quantity, buying thousands of user licenses, results of this research show that the majority fall short in meeting the expectations of their promise. For example, in many cases, IT executives find themselves forced into a position where they have to make decisions before all the information they need is available (76 percent), believe that BI reports end up being simply reference documents to justify decisions that have already been made (63 percent), and do not receive reports that provide predictions about potential problems or provide potential opportunities (more than 70 percent).
The impact of inadequate intelligence on the business is huge. The average cost - discovered by the research – in lost revenue to an organization is $478,686. In fact, one operations manager admitted to a direct $5,000,000 cost to his area of the business. By extrapolating this annual average as representative across the market, then the survey indicates that the Fortune 500 companies are losing approximately $250 million per year in missed business opportunities as a result of inadequate business intelligence.
A study conducted by market research firm Dynamic Markets has today revealed that business intelligence systems are failing to improve operational performance, or impact decision making within US and UK businesses. The research, based on interviews with 218 operational executives and front line management and conducted between November 2006 and August 2007, provides a snapshot of current use and satisfaction with Business Intelligence systems and their impact on operational performance. Although many organizations have deployed BI tools in quantity, buying thousands of user licenses, results of this research show that the majority fall short in meeting the expectations of their promise. The results of this research are shocking: 
Software, commented: "What is clear from this research is that all is not well in the world of BI. BI tools are perceived as hard to use, reports are out of date and largely irrelevant to daily operational decision making; and BI is seen as inherently retrospective. Yet it is clear that managers strive for more, seeking information that can make a difference; that is relevant to operations now; that can give early warning of problems; or can present opportunities for the business." Although managers were very aware of the problems that exist with their current BI solutions, they were also aware of the potential benefits of moving to event driven approaches that provide real time operational 'event intelligence' rather than retrospective 'business' intelligence. Almost all managers surveyed (90%) believed that there would be significant benefits to the business if they could embed greater intelligence into daily operational processes, Benefits mentioned included: 
This article, a follow-up to a previous article published in the June 2003 issue of DM Review, "The Limits of Business Intelligence: An Organizational Learning Approach," looks at how designers can reference organizational theory to more effectively implement BI systems. There are two key areas where designers can exercise leverage over BI implementation to help assure their success:
There are many ways that learning occurs in an organization. Chris Argyris and Donald Schon, scholars at Harvard and MIT respectively, have articulated a useful learning framework.1 They describe organizational learning as comprising single-loop and double-loop modes of change. Single-loop learning occurs when an organization encounters a situation that it can resolve using its current systems, ideas and values. Double-loop learning requires a revision of these artifacts and assumptions. Argyris and Schon also define a third construct, the organization's action theory that describes the collective task knowledge of the organization that it and individuals within the organization access to respond to events. The action theory consists of both explicit knowledge that everyone sees and knows about and tacit knowledge that describes why people actually do what they do in the organization (i.e., it is the organization's collective "moxie").
In the single-loop learning mode, an organization inquires into a situation by referencing its current action theory or repository of institutional knowledge and memory. This can include the collective systems and information resources of the organization, its espoused (public) values, and its basic underlying values and assumptions – the components of institutional memory. In single-loop learning, members of the organization know these things and they are not questioned or changed as the situation is resolved. Figure 1 illustrates how single-loop learning works.
Figure 1: Single-Loop Learning
Here, a single feedback loop, mediated by inquiry into the current organizational knowledge base, connects an outcome of action mismatched by expectations (i.e., negative feedback) that is, therefore, surprising to the organization.2 This is similar to how a room thermostat works. The temperature deviates from some preset level, and it triggers the furnace to kick in until the room temperature rises to the preset level again. In a business example, perhaps sales drop for a quarter and management responds with the usual tactics: cut prices, increase advertising, etc. When sales respond, the intervention is deemed successful. No major changes have been incorporated into the business as a result. The situation has responded to tactics dictated by the current action theory. Single-loop learning thus accommodates and responds to negative feedback from the business environment.
My experience has been that many BI efforts are intended to address a single-loop learning/change situation. Users and technicians design a data warehouse (DW) that feeds data into functional data marts and/or "cubes" of data for query and analysis by BI users. The functional data marts represent business domains such as marketing, finance, production and planning. These are used by functional analysts and managers to inquire into current operating issues and to facilitate incremental improvements and plans. This is seen in Figure 2, a diagram similar to those used by BI vendors to illustrate how BI informs the overall organizational learning process. Figure 2 is a single-loop model of learning.
Figure 2: BI Single-Loop Learning Model
In contrast, a double-loop learning event results in a change to the organization's action theory and its knowledge base. This is shown in Figure 3.
Figure 3: Double-Loop Learning
An additional learning loop connects the observed events with the strategies needed to formulate action (i.e., positive feedback). The action theory and even the knowledge base can undergo revision, as shown in Figure 3. In BI terms, this means that the business intends to integrate the BI technology in such a way as to change its operating model, not just to seek incremental improvement.
In the BI world, examples of double-loop implementation are more difficult to find and are risky when attempted. I can think of one case that I observed where a company planned to use its BI system (a CRM analytic DW) to enable it to migrate to performance-based pricing with its customers. In this case, the BI suite was a technical success but the company did not sell its customers on the pricing idea, nor did its management follow through with the organizational changes needed to accomplish the goal. The end result was that the BI suite was an expensive tool that did not give the business the strategic competitive edge it sought from the technology. It is a lot easier to talk about BI technology changing the business operating model than it is to attempt it when the time comes!
Single-loop methods are workable when inquiry and corrective action take place within the framework of values and norms dictated by the current action theory. However, when events require the organization to revise its action theory so that a new theory is available to members, double-loop learning is needed. The process of inquiry between the organization and its environment, including double-loop type events that result in changes to the action theory, puts a lot of stress on managers and technical staff who must support this mode with BI. It is much more risky. Double-loop organizational learning is becoming a necessity for organizations when environmental change is rapid and disruptive.
For the BI designer, this means that he/she has to assess the level of change and learning that the BI suite is intended to support and then to factor that into the BI project risk. If the BI suite will support a change in the organization's action theory (double-loop change), then there are a lot of factors that will be outside of the BI designer's scope of control but will be necessary to assure the success of the project. These might include changes in organization structure, metrics, compensation formulas and so forth. For example, an enterprise CRM system that includes an analytic DW component integrated with channel contact applications is a project that is likely to be double-loop in scope. According to the industry statistics I have seen, such projects do not have a good track record of success. The rubric about people, processes and technology needing to be in alignment has never been more true when it comes to double-loop change situations!
An organizational learning framework for successfully implementing BI change will have to consider both: the type of change that the BI system is intended to support (single- or double-loop) and, how the components of organizational knowledge (institutional memory) are affected. Before presenting this framework, I want to review how organizations store and process knowledge.
Earlier, I described the construct of the action theory that consists of both explicit knowledge that everyone sees and knows about and tacit knowledge that describes why people actually do what they do in an organization. In my prior article, I discussed the structure of organizational knowledge as seen in Figure 4.
Figure 4: Action Theory Encoded in Organizational Knowledge
Figure 4 illustrates that the action theory is "encoded" in a schema of three levels of knowledge that comprise the organization's institutional memory.3Artifacts are the visible and tangible products of culture in an organization and include items such as the physical layout, reward systems, important business processes, information systems (e.g., the BI suite), symbols of status, logos and dress codes. Espoused values are what people in the organization say that they believe; they are the organization's official view of itself and usually come into being as a result of management action (e.g., a mission statement or promotion of people who exemplify some desired behavior). Finally, basic assumptions are the real operative principles that underlay a culture. Basic assumptions tell the members of the organization what to pay attention to, how to react emotionally, and what to do in various situations; they are embedded in the organization's unconscious knowledge and are less visible. All of these are the repository for explicit and implicit rules that comprise the organization's action theory and, depending on the level of change that a BI project entails, need to be considered.
Figure 5 is a framework for BI designers to assess the level of change and risk that a project requires and to plan accordingly for implementation. The framework shows the scope of the learning or change effort for a BI implementation (single-loop and double-loop) matched to the levels of organizational knowledge that the effort entails.
Figure 5: Framework for BI Change
For example, a data mart that is used for financial analysis by a few users would likely involve only single-loop change; it is not changing the organization's business model or impacting many other users. Thus, its impact is mainly at the artifact level of technology and business processes. My guess is that most departmental BI projects fall into this category and are represented in the lower left-hand corner of the diagram in Figure 5.
In contrast, BI projects that initiate double-loop learning impact the more nebulous levels of organizational knowledge and are represented by the right-hand side of Figure 5. An enterprise CRM system that connects an analytic DW to e-business contact channels such as a user Web site, a contact center and a sales force automation application is likely to involve a lot more organizational change. This type of system could provide both the information and functionality that changes the organization's view of itself and its environment. It will impact the levels of artifacts, espoused values (there might be quality standards involved, especially with customer service functions) and possibly even basic assumptions (e.g., moving to a relationship pricing model with customers). Thus, the project that implements this level of change will need to consider the impact on the higher and more nebulous levels of institutional knowledge. This is represented in the upper right-hand corner of Figure 5. Working at this level of organizational change is sometimes referred to as organization development or OD. The main issue for BI implementers working at this level is to help senior managers to understand what their basic assumptions actually are and how the BI project is likely to influence them (and vice versa).
In short, the BI implementer is faced with the task of assessing the degree of change that a project will require in the target organization and factoring this into his/her plans. The more that a BI project impacts knowledge levels above that of artifacts, the more change effort is required of the organization and on the part of BI project leadership to assure success. Planning and budgeting for the organizational impact of BI, especially when it involves double-loop learning, can greatly increase the likelihood of success of the BI project as a business initiative.
In this article, I have attempted to explain how designers can plan for successful BI implementation using the constructs of organization theory. There are two key areas where designers can exercise leverage over BI implementation to help assure success:
This is accomplished by assessing whether the change that is needed for BI can be accommodated within the organization's current schema of knowledge (single-loop learning) or requires a revision of the schema (double-loop learning). Subsequently, BI designers have to focus change efforts at the right levels of knowledge within the organizations' collective or institutional memory.
