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Business Intelligence Chapter 1: Introduction to Business Intelligence Matthew J. Liberatore Fall 2009 Learning Objectives Understand today’s turbulent business environment and describe how organizations survive and even excel in such an environment (solving problems and exploiting opportunities) Understand the need for computerized support of managerial decision making Describe the business intelligence/business analytics methodology Understand the major issues in implementing business analytics Introduction Business environment is changing, and its become more complex (pressures). Force them to respond quickly. To take a quick decisions they need a relevant amount of data, information and knowledge. Changing Business Environments and Computerized Decision Support The Business Pressures-Responses-Support Model The business environment Organizational responses: be reactive, anticipative, adaptive, and proactive Computerized support • Closing the Strategy Gap One of the major objectives of BI is to facilitate closing the gap between the current performance of an organization and its desired performance as expressed in its mission, objectives, and goals and the strategy for achieving them Changing Business Environments and Computerized Decision Support Business Environment Factors FACTOR Markets Consumer demand Technology Societal DESCRIPTION Strong competition Expanding global markets Blooming electronic markets on the Internet Innovative marketing methods Opportunities for outsourcing with IT support Need for real-time, on-demand transactions Desire for customization Desire for quality, diversity of products, and speed of delivery Customers getting powerful and less loyal More innovations, new products, and new services Increasing obsolescence rate Increasing information overload Social networking, Web 2.0 and beyond Growing government regulations and deregulation Workforce more diversified, older, and composed of more women Prime concerns of homeland security and terrorist attacks Necessity of Sarbanes-Oxley Act and other reporting-related legislation Increasing social responsibility of companies Greater emphasis on sustainability A Framework for Business Intelligence (BI) business intelligence (BI) A conceptual framework for decision support. It combines architecture, databases (or data warehouse), analytical tools and applications . BI Objective: enable interactive access to data to enable manipulation of data and to give business managers to take a good decision. A Framework for Business Intelligence A Brief History of BI The term BI was coined by the Gartner Group in the mid-1990s However, the concept is much older 1970s - MIS reporting - static/periodic reports 1980s - Executive Information Systems (EIS) 1990s - OLAP, dynamic, multidimensional, ad-hoc reporting -> coining of the term “BI” 2005+ Inclusion of AI (Artificial Intelligent) and Data/Text Mining capabilities; Web-based Portals/Dashboards 2010s - yet to be seen A Framework for Business Intelligence (BI) The Origins and Drivers of Business Intelligence Organizations are being compelled to capture, understand, and harness their data to support decision making in order to improve business operations Managers need the right information at the right time and in the right place A Framework for Business Intelligence (BI) BI’s Architecture and Components Data Warehouse Business Analytics Business Performance Management (BPM) User Interface A Framework for Business Intelligence (BI) A Framework for Business Intelligence (BI) BI’s Architecture and Components Data Warehouse (Data Sources) • Data obtained from operational systems needed to support decision making A Framework for Business Intelligence (BI) BI’s Architecture and Components Business Analytics -a collection of tools for manipulating, mining, and analyzing the data in the data warehouse; • Create on-demand reports and queries and analyze data (originally called Online Analytical Processing – OLAP) • Automated decision systems: rule – based App. Case 1.1 – price setting example • Data Mining: a class of information analysis based on databases that looks for hidden patterns in a collection of data which can be used to predict future behavior A Framework for Business Intelligence (BI) BI’s Architecture and Components business (or corporate) performance management (BPM) A component of BI based on the balanced scorecard methodology, which is a framework for defining, implementing, and managing an enterprise’s business strategy by linking objectives with factual measures (Monitoring , measuring and comparing ) A Framework for Business Intelligence (BI) BI’s Architecture and Components User Interface: Dashboards and Other Information Broadcasting Tools • Dashboards A visual presentation of critical data for executives to view. It allows executives to see hot spots in seconds and explore the situation Examples of dashboards and scorecards: http://www.idashboards.com/?gclid=CIDDrpLR05QC FQNaFQodSWDQkQ A Framework for Business Intelligence (BI) The Benefits of BI Time savings Single version of truth Improved strategies and plans Improved tactical decisions More efficient processes Cost savings Faster, more accurate reporting Improved decision making Improved customer service Increased revenue Many benefits are intangible Automated Decision Making (ADS) It’s a rule based systems that provide a solution, usually in one functional area E.g.( finance, manufacturing ) to a specific repetitive managerial problem. Its used in the Airline industry, dynamicly price ticket based on demands. Event-Driven Alerts Its an example of ADS, which is a warning or action that is activated when a predefined or unusual event occur. For example: credit card comp. make a predictive analysis models to identify cases possible fraud. Intelligence Creation and Use Steps Involved Data warehouse deployment Creation of intelligence Identification and prioritization of BI projects By using ROI and TCO (cost-benefit analysis) This process is also called BI governance BI Governance Who should do the prioritization? Partnership between functional area heads and leaders(middles) Partnership between customers and providers BI Governance Issues/Tasks 1. Create categories of projects (investment, business opportunity, strategic, mandatory, etc.) 2. Define criteria for project selection 3. Determine and set a framework for managing project risk 4. Manage and leverage project interdependencies 5. Continuously monitor and adjust the composition of the portfolio Intelligence and Espionage Stealing corporate secrets, CIA, … Intelligence vs. Espionage Intelligence The way that modern companies ethically and legally organize themselves to glean as much as they can from their customers, their business environment, their stakeholders, their business processes, their competitors, and other such sources of potentially valuable information Problem – too much data, very little value Use of data/text/Web mining (see Chapter 4, 5) Transaction Processing Versus Analytic Processing (OLTP Vs OLAP) Transaction processing systems are constantly involved in handling updates (add/edit/delete) to what we might call operational databases. ATM withdrawal transaction, sales order entry via an ecommerce site – updates DBs Online analytic processing (OLTP) handles routine ongoing business ERP, SCM, CRM systems generate and store data in OLTP systems The main goal is to have high efficiency Transaction Processing Versus Analytic Processing Online analytic processing (OLAP) systems are involved in extracting information from data stored by OLTP systems Routine sales reports by product, by region, by sales person, etc. Often built on top of a data warehouse where the data is not transactional Main goal is effectiveness (and then, efficiency) – provide correct information in a timely manner More on OLAP will be covered in Chapter 2 1.5 Successful BI Implementation Impelementing BI can be lengthy, expensive and failure. The Typical BI User: the successful of BI must benefit to the enterprise as whole. - Many of whom should be involved from the outset of (DW “datawarehouse). Appropriate Planning and Alignment with Business Strategy To be successful, BI must be aligned with the company’s business strategy. BI cannot/should not be a technical exercise for the information systems department. BI changes the way a company conducts business by: improving business processes, and transforming decision making to a more data/fact/information driven activity. BI should help execute the business strategy and not be an impediment for it! Real-time, On-demand BI The demand for “real-time” BI is growing! Is “real-time” BI attainable? Technology is getting there… Automated, faster data collection (RFID, sensors,… ) Database and other software technologies (agent, SOA, …) are advancing Telecommunication infrastructure is improving Computational power is increasing while the cost for these technologies is decreasing Trent -> Business Activity Management Issues for Successful BI Developing vs. Acquiring BI systems Developing everything from scratch Buying/leasing a complete system Using a shell BI system and customizing it Use of outside consultants? Justifying via cost-benefit analysis It is easier to quantify costs Harder to quantify benefits Most of them are intangibles Issues for Successful BI Security and Privacy Still an important research topic in BI How much security/privacy? Integration of Systems and pplications BI must integrate into the existing IS - Often sits on top of ERP, SCM, CRM systems Integration to outside (partners of the extended enterprise) via internet – - customers, vendors, government agencies, etc. Major BI Tools and Techniques Tool categories Data management Reporting, status tracking Visualization Strategy and performance management Business analytics Social networking & Web 2.0 New/advanced tools/techniques to handle massive data sets for knowledge discovery