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Introduction to Business Intelligence

Introduction to Business Intelligence. 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

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Introduction to Business Intelligence

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  1. Introduction to Business Intelligence

  2. 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

  3. Changing Business Environments and Computerized Decision Support

  4. Businesses are always fraught with challenges Managers must make decisions almost on a daily basis Many of those decisions have significant financial and organizational impact Examples: What tools can we use to make the decisions efficiently (not waste too much time and resources) and more effective (have greater impact on the final outcome) Managerial Decision Making

  5. Nobel Laureate Herbert Simon postulated that rational decision maker goes through the following stages: Decision Making Process

  6. Systems Prior to BI • Decision Support Systems • Mainly model based. Supports the design part with limited support for the choice part of decision making • Statistical Tools • More data oriented. Provides data descriptions and insight into the data. • Data Mining • Specialized data analysis tools for structured data analysis • Knowledge Management • Tools for capturing and managing knowledge. Can be considered as pre-cursor to BI

  7. Business Intelligence (BI) • Business Intelligence (BI) • A conceptual framework for an integrated decision support environment. It combines architecture, databases (or data warehouse), analytical and visual presentation tools. • The success of a BI solution ultimately is determined by how well it helps both business and technical users throughout an organization meet their mission critical goals.

  8. The 5 Stages of Business Intelligence • BI development typically follows the 5 stages listed below: • 1. The Data: defining which data will be loaded into the system and analyzed. • 2. The ETL (Extract, Transform, and Load) Engine: moving the source data to the Data Warehouse. This can be a complex step involving modifications and calculations on the data itself. If this step doesn’t work properly, the BI solution simply cannot be effective. • 3. Data Warehousing: connects electronic data from different operational systems so that the data can be queried and analyzed over time for business decision making. • 4. Analytic Engine: analyzes multidimensional data sets found in a data warehouse to identify trends, outliers, and patterns. • 5. Presentation Layer: the dashboards, reports and alerts that present findings from the analysis.

  9. A Framework for Business Intelligence (BI)

  10. BI Components • Data Warehouses and 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 • 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 • Dashboards • A visual presentation of critical data for executives to view. It allows executives to see hot spots in seconds and explore the situation

  11. Business Intelligence: A Confluence of Tools and Capabilities • The three circles of the Venn diagram each represent (previously considered) distinct areas of study and application: • 1.information systems and technology, • 2. statistics, and • 3. OR/MS. • BI can be described as a combination of : business information intelligence (BII), business statistical intelligence (BSI) and business modeling intelligence (BMI). • BI must provide an integrated capabilities for decision making and those include capabilities for • Collection • Description • Prescription • Interpretation

  12. BI vs. Business Analytics • Used often interchangeably in the present business environment • Analytics is more tools oriented, so it mainly refers to the technology for BI • BI is more of the umbrella term that also includes the business side of the equation • BI is more of a planning level concept and BA is more of an implementation level concept • If you think of KPI (Key Performance Indicators), BI defines them while BA measures them (roughly speaking) • Google Analytics: BI or BA?

  13. Major BI Vendors • List obtained from: • http://www.business-software.com/business-intelligence-solutions/business-intelligence/index.php • Leading Vendors are: • Actuate • Cognos • Information Builders • Microsoft • MicroStrategy • Oracle • Panorama • QlikTech • SAP • SAS • Go to the website listed above, and then investigate the strengths and weaknesses of the BI products from each of the vendors and create a 2-4 page comparison report. Identify also the major area of thrust for each of the vendors

  14. Challenges for BI Implementation • Multi-process, multi-users environment • The Typical BI User Community • IT staff • Power users • Executives • Functional managers • Occasional information customers • Partners • Consumers

  15. Challenges for BI Implementation • Lack of a Complete and Integrated Single Vendor Solution • Some progress are being made though with SaaS model and In-Memory BI

  16. Challenges for BI Implementation • Lack of integration with Organizational Strategy • BI is viewed more as a technology than an organizational process change and strategic initiative • Lack of data standardization • Rapidly growing volume of data • Rapidly changing technology • Need for specialized knowledge and training • Security and legal issues associated with information access and use

  17. BI Governance • BI Governance consists of • The project prioritization process within organizations • Creating categories of projects (investment, business opportunity, strategic, mandatory, etc. • Defining criteria for project selection • Determining and setting a framework for managing project risk • Managing and leveraging project interdependencies • Continually monitoring and adjusting the composition of the portfolio • Intelligence Gathering that involves how modern companies ethically and legally organize themselves to glean as much information as they can from their: • Customers • Business environment • Stakeholders • Business processes • Competitors • Other sources of potentially valuable information • Setting processes instead of just solutions

  18. BI Governance

  19. Strategic, Tactical & Functional Benefits of Business Intelligence

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