1. 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.

2. A hotel franchise uses BI analytical applications to compile statistics on average occupancy and average room rate to determine revenue generated per room. It also gathers statistics on market share and data from customer surveys from each hotel to determine its competitive position in various markets. Such trends can be analyzed year by year, month by month and day by day, giving the corporation a picture of how each individual hotel is faring. A bank bridges a legacy database with departmental databases, giving branch managers and other users access to BI applications to determine who the most profitable customers are or which customers they should try to cross-sell new products to. The use of these tools frees information technology staff from the task of generating analytical reports for the departments and it gives department personnel autonomous access to a richer data source. 3. Today's exciting BI market is ripe with opportunities to hit your strategic business targets. Gaining market share, keeping customers and controlling costs remain key objectives. Mid-market executives and big corporate department heads rush to cost effectively meet these complex needs. How? Through improved use of their existing database systems. CFOs require 'business intelligence' systems that display accurate SKU or customer-level P&Ls, permitting reliable channel and store comparisons over time. Improved forecasts are vital, too! Data warehousing and analytical skills are combined with an understanding of industry issues, as we refine and implement your vision. According to Gartner survey of 1,400 CIOs, business intelligence was ranked the top technology priority surpassing security. The BI and analytics market is currently valued at $8.5 Billion and is expected to grow to $13 Billion over the next five years 4. Reduce labor costs Reduce information bottlenecks Make data actionable Better decisions Faster decisions Align the organizations towards its business objectives New insights 5. Subject-oriented Unified, centrally managed subject definitions and targets System guided data interaction and exploration Automated data collection and distribution System supported data documentation and validation 6. All data in the BI system must be interfaced using natural terms corresponding to the organization's business' reality. For example, users of the BI system must be able to access data in the BI system using natural terms such as "Customer" and "Sales amount" rather than for example table and field names in the database. 7. All definitions of business terms and KPIs must exist in one version only and they must be managed from a central point to avoid redundant definitions, reports referring to outdated definitions etc. This requirement implies that application of data and definition of data must be separated by the system into a so-called semantic layer. 8. Interaction with data and data exploration are two vital features of a BI system that allow users to answer questions fast and autonomously. Many tools offer ways to manipulate data, but it is important to notice the term guided interaction/exploration. A system can only guide the user if it has some knowledge about the data. As an example of what is notmeant by guided, consider a query designer: It lets the user draw relations between tables and fields in a database in order to manipulate the output. 9. In order to achieve the benefits of reduced labor costs and faster decisions, all data collection must be automated. notice, that if the BI system extracts its data directly from the operational systems then the requirement of automated data collection is implicitly met. 10. The users don't understand the contents of the report and as a result they don't use it Users think they understand the contents and use the report. But they make the wrong decisions from time to time because the data is not what they think it is. When data looks wrong, one needs to investigate and validate it. But if there is no documentation of how and when the data was collected and aggregated then it can be impossible for the user to validate the results. As a result the user will resort to other sources of data. 11. BI is neither a product nor a system. It is an architecture and a collection of integrated operational as well as decision support applications and databases that provide the business community easy access to business data. 12. Better decisions with greater speed and confidence Recognize and maximize firms strengths Shorten marketing efforts Improve customer relationships Align effort with firm strategy Improve revenue and profit 13. Improve Management Processes planning, controlling, measuring and/or changing resulting in increased revenues and reduced costs Improve Operational Processes fraud detection, order processing, purchasing.. resulting in increased revenues and reduced costs Predict the Future 14. Top 10 Business and Technology Priorities for 2011: Cloud computing Virtualization Mobile technologies IT Management Business Intelligence Networking, voice and data communications Enterprise applications Collaboration technologies Infrastructure Web 2.0 15. Making Business Decisions is a Balance Data Opinion 16. Business Intelligence Business Analytics What happened? Why did it happen? When? Will it happen again? Who? What will happen if we change? How many? What else does the data tell us that never thought to ask? 17. Data Sourcing Data Analysis Situation Awareness Risk Analysis Decision Support 18. AQL Associated Query Logic Balanced Scorecard Business Activity Monitoring Business Performance Management Business Planning Business Process Re-engineering Competitive Analysis User/End-User Query and Reporting Enterprise Management System Executive Information System SCM Supply Chain Management Demand Chain Management Finance and Budgeting tools. 19. The BI model must contain these parts: Data model. A set of subject definitions and interrelations that describe the name, purpose, construction and inter-relation of all relevant business data terms. E.g. "Customer", "Item group", "Sales Amount" etc. This part corresponds to a MDD and its components, Dimensions and Metrics. Rule model. A set of rules that describe thresholds of KPIs, potential business actions and business events. For example a rule can describe under which threshold a KPI - say Profit Margin Percent - is not acceptable and what the user could/should do about it. Rules can be associated with highlighting information such as colors and icons plus a descriptive text that is displayed in the viewing context, i.e. inside reports. Process model. The process model relates reports to users and reports with other reports. The process model ensures relevance by giving each user access to exactly the data that user needs in any context, not less and not more. For example, the process model describes which report/dashboard must be opened automatically when the user connects to the system. And it describes how data in one report can be linked to other reports. 20. Data Mining, Framing & Warehousing (DSS) and Forecasting Document Warehouse & Management Knowledge Management Mapping, Information Visualization and Dash boarding; Management Information System (MIS); Geographic Information System (GIS); Trend Analysis; Software As A Service (SaaS) Business Intelligence offerings (On Demand) Online Analytical Processing (OLAP) and Multidimensional analysis sometimes called "Analytics" (based on the "hypercube" or "cube"); Real Time Business Intelligence Statistics and Technical Data Analysis Web Mining, Text Mining and Systems Intelligence 21. Factors need to be considered Goal Alignment queries Baseline queries Cost and risk queries Customer and Stakeholder queries Metrics-related queries Measurement Methodology-related queries Results-related queries 22. BI 2.0" is the recently-coined term which is part of the continually developing BI industry and heralds the next step for BI. BI 2.0 is used to describe the acquisition, provision and analysis of "real time" data.