The document discusses the significance and applications of business intelligence (BI) in various industries, highlighting its role in analyzing data to improve decision-making. It emphasizes the importance of BI systems in providing timely and accurate information regarding customers, market trends, and competitors, ultimately aiding companies in gaining a competitive advantage. The future of BI focuses on real-time data access and the challenges associated with achieving this capability amidst varying business structures and data sources.

1. Business Intelligence (BI)

2. Business Intelligence…examples 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. A telecommunications company maintains a multiterabyte decision-support data warehouse and uses business intelligence tools and utilities to let users access the data they need without giving them carte blanche to access hundreds of thousands of mission-critical records. The tools set boundaries around the data that users can access, creating data "cubes" that contain only the information that's relevant to a particular user or group of users.

3. BI Industry Scenario… 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. Business Intelligence (BI) BI refers to application and technology, which is used to gather, provide access to, and analyze data and information about the company operations

5. Business Intelligence Definition 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.

6. BI Popularized… In 1989 Howard Dresner a Research Fellow at Gartner Group popularized "BI" as an umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems

7. Why BI solutions ?

8. More data and data sources…

9. Evolution from Static Report to BI…

10. Evolution of financial Systems…

11. Categories of Report Writers

12. Sources of Information for Vendor & Product Research

13. Key Stages of BI Data Sourcing Data Analysis Situation Awareness Risk Analysis Decision Support

14. BI applications and technologies can help companies analyze: changing trends in market share changes in customer behavior and spending patterns customers' preferences company capabilities market conditions

15. Significance of BI… To know about Customers Having access to timely and accurate information is an important resource for a company, which can expedite decision-making and improve customers' experience. In the competitive customer-service sector, companies need to have accurate, up-to-date information on customer preferences, so that the company can quickly adapt to their changing demands. BI enables companies to gather information on the trends in the marketplace and come up with innovative products or services in anticipation of customer's changing demands.

16. Significance of BI… To know about Competitors…Market… BI applications can also help managers to be better informed about actions that a company's competitors are taking. BI systems can also be designed to provide managers with information on the state of economic trends or marketplace factors, or to provide managers with in depth knowledge about the internal operations of a business.

17. Significance of BI… For avoiding Guesswork… BI can be used to help analysts and managers determine which adjustments are most likely to respond to changing trends. BI systems can help companies develop a more consistent, data-based decision making process for business decisions, which can produce better results than making business decisions by "guesswork."

18. Significance of BI… For sharing of information… BI can help companies share selected strategic information with business partners. Some businesses use BI systems to share information with their suppliers like….. inventory levels performance metrics other supply chain data

19. Significance of BI… For improving performance… BI applications can enhance communication among departments, coordinate activities, and enable companies to respond more quickly to changes (e.g., in financial conditions, customer preferences, supply chain operations, etc.). When a BI system is well-designed and properly integrated into a company's processes and decision-making process, it may be able to improve a company's performance.

20. BI Technologies need to have a secure computer system which can specify different levels of user access to the data 'warehouse', need to have sufficient data capacity, a plan for how long data will be stored (data retention). BI analysts have developed software tools to gather and analyze large quantities of unstructured data such as production metrics, sales statistics, attendance reports, customer attrition figures.

21. BI Tools AQL – Associatede 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 and Finance and Budgeting tools.

22. Other BI applications are used to store and analyze data Data Mining, Framing & Warehousing (DSS) and Forecasting Document Warehouse & Manage,ment Knowledge Management Mapping, Information Visualisation and Dashboarding; 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 Statastics and Technical Data Analysis Web Mining, Text Mining and Systems Intelligence

23. Other BI applications are used to analyze or manage the "human" side of businesses , Customer Relationship Management (CRM) Marketing Tools Human Resources applications. Web Personalisatiuon

24. Some common factors of ill-equipped organizations to implement BI… Lack of understanding of the complexity of BI decision-support projects Lack of recognizing BI decision-support projects as cross-organizational business initiatives and not understanding that cross-organizational initiatives are different from stand-alone solutions Unavailable or unwilling business representatives Unengaged business sponsors or business sponsors who have little or no authority due to their low-level positions within the organization

25. Some common factors of ill-equipped organizations to implement BI… Lack of skilled and available staff as well as suboptimum staff utilization Inappropriate project team structure and dynamics No software release concept (no iterative development method) No work breakdown structure (no methodology) Ineffective project management (only project administration) No business analysis and no standardization activities No appreciation of the impact of dirty data on business profitability No understanding of the necessity for and the usage of meta data Too much reliance on disparate methods and tools (the "silver bullet" syndrome)

26. Designing and implementing a Business Intelligence Program 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

27. The Future of BI… BI users are beginning to demand [Real time BI] or near real time analysis relating to their business, particularly in front line operations. They will come to expect up to date and fresh information in the same fashion as they monitor stock quotes online. Monthly and even weekly analysis will not suffice

28. The Future of BI… "Business users don't want to wait for information. Information needs to be always on and never out of date. This is the way we live our lives today. Why should Business Intelligence be any different?" Charles Nicholls, CEO of SeeWhy, a Software company, Windsor UK

29. The Future of BI… In the not too distant future companies will become dependent on real time business information in much the same fashion as people come to expect to get information on the internet in just one or two clicks. "This instant "Internet experience" will create the new framework for business intelligence, but business processes will have to change to accommodate and exploit the real-time flows of business data." Nigel Stokes, CEO, DataMirror Corp.

30. BI 2.0 “ 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.

31. "Real Time BI - Get Real" "The mismatch between fantasy and reality is driven by two factors. The first is that business rules and structures (general ledgers, product classification, asset hierarchies, etc.) are not in fact uniform, but are spread out among many disparate transaction system implementations... The second problem is that the landscape of business structures is itself in constant flux, as groups reorganize, subsidiaries are sold or new companies acquired". … Veteran Analyst… Andy Hayler…

32. "Real Time BI…a pipe dream” As long as Business Intelligence relies upon some kind of data warehouse structure (including web-based virtual data "warehouses"), data will have to be converted into "a lowest common denominator consistent set." When it comes to dealing with multiple, disparate data sources and the constantly changing, often volatile, business environment which requires tweaking and restructuring of IT systems, getting BI data in a genuinely true, "real time" format remains, "a pipe dream.....Hayler

33. Thank You! Piyush Mehta [email_address]

34. 1KEY – Data 2 Decision Does your IT Infrastructure keep up with the changing needs and demand? Does your IT system help to provide business transformation and leadership? Do your organisation not dependent on spreadsheets for mass reporting? Don’t you feel at the mid-sea of database without direction to get useful information out of that? Does your Organisation mass reporting system work at the speed of thoughts? Do your technology capable of creating magic? There is one solution to all your above questions…….. 1KEY BI Software Product from MAIA Intelligence