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  1. 1. Business Intelligence<br />Presented by:<br />Vijaykanth.R<br />Venkatakondan.R<br />
  2. 2. Introduction<br />BI refers to application and technology, which is used to gather, provide access to, and analyze data and information about the company operations <br />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<br />
  3. 3. History Of Business Intelligence<br />in 1979, John Rockart published the article “Chief Executives Define Their Own Data Needs” proposing that systems used by corporate leaders ought to give them data about the key jobs the company must do well to succeed. <br />Ten years later, in 1999, Howard Dresner coined the term “business intelligence” to describe systems that help decision makers throughout the organization understand the state of their company’s world.<br />In January 2006, Thomas Davenport published the results of a two year study “Competing on Analytics”. His research identified that virtually all the organizations identified as “aggressive analytics competitors” were the clear leaders in their fields, and they attribute much of their success to the masterful exploitation of data. Such companies included: Tesco, Wal-Mart, Dell, Marriott Hotels and Progressive Insurance.<br />
  4. 4. How do I make decissions<br />in my business? <br />• How does the company make decissions? Using <br />intuition? You have to make business decisions based <br />on reality (facts and numbers!) <br />• EPM (Enterprise Performance Management) is a <br />management style focused on measuring companies <br />• Several Methodologies / Strategies: <br />• Balanced Scorecard <br />• Six Sigma, ABC - Activity Based Costing, TQM - Total Quality Management <br />
  5. 5. Types of decisions<br />Structured<br />Semi structured<br />Non structured<br />Strategic<br />Tactic<br />Operational<br />
  6. 6. Business Problem <br />• Where is the problem? <br />• Marketing Mgr is right: the data IS in the servers <br />• IT Mgr is also right: is not easy to give data the right structure to answers questions <br /> <br />• For IT is just enough to deal with data, Marketing needs to extract information from this data.<br />
  7. 7. Data and information are not the same <br /> <br />• Companies always maintain several systems to run their everyday business <br /> <br />• All of the company workers add and check data from this systems all the time <br /> <br />• However sometimes this data, presented in this way, is not enough to make business decisions <br />
  8. 8. objectives<br />Identify market opportunities<br />Know where market share is unsatisfactory<br />Better understand their profitability drivers<br />Identify unacceptable cost areas<br />Gain an accurate view of sale and/or distribution costs, per channel, per customer, per transaction, per day<br />Recognize business areas of high performance<br />Identify the key performance indicators [KPI's] to use to measure capability<br />Calculate sales commissions, number of sales closed, highlight good and poor performers<br />Track whether strategies for certain markets or customers are working and driving business value<br />Get instant insight to the exact profit by company of each sale<br />
  9. 9. What is Business Intelligence (BI)?<br />IT-enabled business decision making based on simple to complex data analysis processes<br />Database development and administration<br />Data mining<br />Data queries and report writing<br />Data analytics and simulations<br />Benchmarking of business performance<br />Dashboards<br />Decision support systems<br />
  10. 10. Why BI?<br />Make more informed business decisions:<br />Competitive and location analysis<br />Customer behavior analysis<br />Targeted marketing and sales strategies<br />Business scenarios and forecasting<br />Business service management<br />Business planning and operation optimization<br />Financial management and compliance<br />
  11. 11. Knowledge of database systems and data warehousing technologies<br />Ability to manage database system integration, implementation and testing<br />Ability to manage relational databases and create complex reports<br />Knowledge and ability to implement data and information policies, security requirements, and state and federal regulations<br />Critical Technology Knowledge and Skills<br />
  12. 12. <ul><li>Understanding of the flow of information throughout the organization
  13. 13. Ability to effectively communicate with and get support from technology and business specialists
  14. 14. Ability to understand the use of data and information in each organizational units
  15. 15. Ability to present data in a user-centric framework
  16. 16. Ability to understand the decision making process and to focus on business objectives
  17. 17. Ability to train business users in information management and interpretation</li></ul>Critical Business and Customer Skills and Knowledge<br />
  18. 18. BI Technologies<br />need to have a secure computer system <br />which can specify different levels of user access to the data 'warehouse', <br />need to have sufficient data capacity, <br />a plan for how long data will be stored <br />(data retention). <br />BI analysts have developed software tools <br />to gather and analyze <br />large quantities of unstructured data such as <br />production metrics, <br />sales statistics, <br />attendance reports,<br />customer attrition figures. <br />
  19. 19. BI Tools<br />AQL – Associatede Query Logic<br />Balanced Scorecard<br />Business Activity MonitoringBusiness Performance Management<br />Business Planning <br />Business Process Re-engineering<br />Competitive Analysis<br />User/End-User Query and Reporting<br />Enterprise Management System<br />Executive Information System<br />SCM – Supply Chain Management<br />Demand Chain Management<br />and <br />Finance and Budgeting tools. <br />
  20. 20. The BI Value Proposition<br />IntelligentInteractions (Data Mining)<br />Predictive<br />Forecasting<br />Fact-Based Actions (OLAP/In-Memory, Statistics )<br />Analysis<br />PerformanceManagement (KPI, Guided Analytics)<br />Are there any potential out-of-stock situations region warehouse wise?<br />Reporting<br />Increasing Value<br />Slice/Dice<br />Ad-hoc Query,<br />BI Tools<br />How is the business doing compared to last year? Compared to plan?<br />Can I understand my gross margin return on space?<br />Transactional<br />Reporting<br />How are my export and domestic sales doing<br />Generational Step<br />
  21. 21. BI – Traditional Models<br />Non-OLAP<br />Data Models<br />(Programming, <br />Visual Query <br />Tools,<br />In-Memory, etc)<br />Real time<br />Reporting<br />
  22. 22. BI – Next Generation BI Flow<br />Operational <br />Business Intelligence<br />Easy-to-use <br />Front-end for <br />Business users<br />Supporting Business Activity Monitoring (BAM)<br />
  23. 23. So What is Business Intelligence?<br />It includes everything :<br />Ad Hoc, Interactive, Visual Reporting<br />Interactive Analysis<br />What-if Analysis<br />Descriptive and Predictive Modeling<br />Need to define ways of inducting BI<br />Every company needs a customized approach<br />
  24. 24. Business Challenges<br />TECHNOLOGY<br />Market Volatility<br />Competition<br />Customer<br />Management<br />Consolidation<br />Manpower<br />Transaction <br />Volume<br />Suppliers<br />Government <br />Reforms<br />
  25. 25. Designing and implementing a Business Intelligence Program<br />Factors need to be considered<br />Goal Alignment queries<br />Baseline queries<br />Cost and risk queries<br />Customer and Stakeholder queries<br />Metrics-related queries<br />Measurement Methodology-related queries<br />Results-related queries<br />
  26. 26. The Future of BI…<br />BI users are beginning to demand <br />[Real time BI] or near real time <br />analysis relating to their business, <br />particularly in front line operations. <br />They will come to expect up to date and fresh information in the same fashion as they monitor stock quotes online. <br />Monthly and even weekly analysis <br />will not suffice<br />
  27. 27. The Future of BI…<br /> "Business users <br />don't want to wait for information. <br />Information needs to be always on <br />and never out of date. <br />This is the way we live our lives today. <br />Why should Business Intelligence be any different?" <br />Charles Nicholls, <br />CEO of SeeWhy, a Software company, Windsor UK<br />
  28. 28. BI 2.0<br /> “BI 2.0" is the recently-coined term which is part of the continually developing BI industry and heralds the next step for BI. <br />“BI 2.0" is used to describe<br />the acquisition, provision <br />and analysis of <br />"real time" data.<br />
  29. 29. "Real Time BI…a pipe dream”<br />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." <br />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, <br />"a pipe dream.....Hayler<br />
  30. 30. "Real Time BI - Get Real"<br />"The mismatch between fantasy and reality is driven by two factors. <br />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...<br />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".<br />…Veteran Analyst… Andy Hayler… <br />