THE ESSENTIALS OF BUSINESS INTELLIGENCE

Slides:



Advertisements
Similar presentations
Module 3: Business Information Systems
Advertisements

Life Science Services and Solutions
Business Intelligence
Database – Part 3 Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Mr. Sakthi Angappamudali.
CISB444 - Strategic Information Systems Planning
Business Intelligence Michael Gross Tina Larsell Chad Anderson.
Database – Part 2b Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Sakthi Angappamudali at Standard Insurance; BI.
Strategic Information Systems for Competitive Advantage
Copyright ©2013 Pearson Education, Inc. publishing as Prentice Hall
Chapter 1 Introduction to Business Intelligence
McGraw-Hill/Irwin Copyright © 2008, The McGraw-Hill Companies, Inc. All rights reserved.
Business Driven Technology Unit 3 Streamlining Business Operations Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution.
Introduction to Business Analytics
CISB594 – Business Intelligence
Business Intelligence System September 2013 BI.
Business Intelligence: Essential of Business
Chapter 8: Development of Business Intelligence
Navision Business Analytics Joyce Leung, Partner Technology Specialist.
Business Intelligence
Certified Business Process Professional (CBPP®) Exam Overview
Information Technology in a Supply Chain
Chapter 2: Business Intelligence Capabilities
Copyright © 2014 Pearson Education, Inc. 1 It's what you learn after you know it all that counts. John Wooden Key Terms and Review (Chapter 6) Enhancing.
Business Intelligence
CHAPTER 8: LEARNING OUTCOMES
Getting Smarter with Information An Information Agenda Approach
ISQS 3358, Business Intelligence Anatomy of Business Intelligence
What is Business Intelligence? Business intelligence (BI) –Range of applications, practices, and technologies for the extraction, translation, integration,
Strategic Information Systems Planning
Module 3: Business Information Systems Chapter 11: Knowledge Management.
Efficient BI Solution Presented by: Leo Khaskin, PowerCubes Lab Value of Information as Business Asset.
1.Knowledge management 2.Online analytical processing 3. 4.Supply chain management 5.Data mining Which of the following is not a major application.
Understanding Data Warehousing
MAJOR BUSINESS INITIATIVES Gaining Competitive Advantage with IT
Business Analysis and Essential Competencies
1 Business Intelligence Strategy and Technologies.
MANAGEMENT SUPPORT SYSTEMS II 7. Business Intelligence.
@ ?!.
Introduction to Business Intelligence
Introduction to Information Technology, 2nd Edition Turban, Rainer & Potter © 2003 John Wiley & Sons, Inc Introduction to Information Technology.
BUSINESS DRIVEN TECHNOLOGY
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc. All rights reserved. 1-1 BUSINESS DRIVEN TECHNOLOGY UNIT 1: Achieving Business Success Through.
CISB594 – Business Intelligence Understanding Business Intelligence Part II.
Chapter 2 Competing with Information Technology. Learning Objectives Identify basic competitive strategies and explain how a business can use IT to confront.
McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved Chapter 9 Enabling the Organization – Decision Making.
Datawarehouse A sneak preview. 2 Data Warehouse Approach An old idea with a new interest: Cheap Computing Power Special Purpose Hardware New Data Structures.
CISB594 – Business Intelligence Business Performance Management.
Information systems and management in business Chapter 8 Business Intelligence (BI)
© 2007 IBM Corporation IBM Information Management Accelerate information on demand with dynamic warehousing April 2007.
© 2010 IBM Corporation Business Analytics software Business Analytics Editable Text Editable Text Editable Text.
Information Systems in Organizations Managing the business: decision-making Growing the business: knowledge management, R&D, and social business.
CISB594 – Business Intelligence Business Performance Management.
Why BI….? Most companies collect a large amount of data from their business operations. To keep track of that information, a business and would need to.
1.1 © 2007 by Prentice Hall 1 Chapter Information Systems in Global Business Today.
ERP and Related Technologies
1 Copyright © Oracle Corporation, All rights reserved. Business Intelligence and Data Warehousing.
ISQS 3358, Business Intelligence Anatomy of Business Intelligence Zhangxi Lin Texas Tech University 1.
1 Management Information Systems M Agung Ali Fikri, SE. MM.
Overview of SAP Application Services By Accely. Introduction Developed organizations in any business industry will invest in SAP programs to offer progressive.
Revision Chapter 1/2/3. Management Information Systems CHAPTER 1: INFORMATION IN BUSINESS SYSTEMS TODAY How information systems are transforming business.
BUSINESS INTELLIGENCE. The new technology for understanding the past & predicting the future … BI is broad category of technologies that allows for gathering,
Introduction to Business Analytics
1 © 2014 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner.
Advanced Applied IT for Business 1
Introduction to Business Intelligence
Management Information Systems
McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved.
Big DATA.
Module 5 Strategic Enterprise Management and Reporting Tools
KEY INITIATIVE Financial Data and Analytics
Presentation transcript:

THE ESSENTIALS OF BUSINESS INTELLIGENCE Chapter S THE ESSENTIALS OF BUSINESS INTELLIGENCE

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 Business cycle times are now extremely compressed; faster, more informed, and better decision making is therefore a competitive imperative Managers need the right information at the right time and in the right place

General Process of Intelligence Creation and Use To be successful in today’s business environment, enterprises must: Assess their readiness for meeting the challenges posed by these new business realities Take a holistic approach to BI functionality Leverage best practices and anticipate hidden costs

General Process of Intelligence Creation and Use Key questions as a framework for BI analysis: How can enterprises maximize their BI investments? What BI functionality do enterprises need, and what are they using today? What are some of the hidden costs associated with BI initiatives?

General Process of Intelligence Creation and Use

General Process of Intelligence Creation and Use Intelligence creation and use and BI governance BI governance Project prioritization process Issues for the BI governance team is to address the following: Creating categories of projects 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

Major Characteristics of Business Intelligence Business intelligence is NOT transaction processing Online analytical processing (OLAP) An information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on. The result is generated in seconds

Major Characteristics of Business Intelligence The information factory view Enterprise information factory as a way to describe how companies conduct and organize BI efforts. A cornerstone component of that factory concept is the DW

Major Characteristics of Business Intelligence An information factory has: Inputs Data sources Acquisition Storage DW Data marts Processing of inputs Analysis Data mining Outputs Data delivery BI applications

Major Characteristics of Business Intelligence

Major Characteristics of Business Intelligence

Major Characteristics of Business Intelligence Data warehousing and business intelligence Create a database infrastructure that is always online and that contains all the information from the OLTP systems, including historical data, but reorganized and structured in such a way that it is fast and efficient for querying, analysis, and decision support

Toward Competitive Intelligence and Advantage Strategic imperative because: Barriers to entry of a new competitor to an industry are being significantly diminished An organization that has a strong position within its industry could easily face new competitors because the costs and other constraints to becoming a player in the market have decreased Due to globalization

Toward Competitive Intelligence and Advantage Competitive intelligence (CI) CI implies tracking what competitors are doing by gathering sources of materials on their recent and in-process activities BI initiatives use some outside sources of data are included in the analysis process, but they are often available from third-party vendors

Toward Competitive Intelligence and Advantage Competitive strategy in an industry Competitor analysis is a component of industry analysis, which serves as a basis for strategic planning processes BI applications in this context might include scrutinizing quality metrics associated with specific production processes, analyzing raw materials from various suppliers to assess defect rates, tracking costs of goods sold as a percentage of run volume, and so on

Toward Competitive Intelligence and Advantage Competitive strategy in an industry Focus on a particular market niche, perhaps through some form of product or service differentiation BI applications in this context might include: Making sure customer needs are met and loyalty is built Tracking and remembering customer preferences in the next customer encounter

Toward Competitive Intelligence and Advantage Sustaining competitive advantage Most strategic analysts agree that low-cost leadership may not yield a sustainable advantage unless the low cost can be sustained BI projects and DW are becoming increasingly important weapons in sustaining competitive advantage across industries

Successful Business Intelligence Implementation The fundamental reasons for investing in BI must be aligned with the company’s business strategy BI must serve as a way to change the manner the company conducts business by improving its business processes and transforming decision-making processes to be more data driven

Successful Business Intelligence Implementation A framework for planning is a necessary precondition At the business and organizational levels, it is important to define strategic and operational objectives while considering the available organizational skills to achieve those objectives Upper managers must build enthusiasm for those initiatives and procedures for the intraorganizational sharing of BI best practices Plans to prepare the organization for change must be in place

Successful Business Intelligence Implementation If a company’s strategy is properly aligned with the reasons for a DW and BI initiatives, if the company’s IS organization is or can be made capable of playing its role in such a project, and if the requisite user community is in place and has the proper motivation, it is wise to start BI and establish a BI competency center (BICC) within the company

Successful Business Intelligence Implementation Attaining real-time, on-demand BI The demand for instant, on-demand access to dispersed information has grown as the need to close the gap between the operational data and strategic objectives has become more pressing New data-generating technologies, such as RFID, is accelerating this growth and the subsequent need for real-time BI

Successful Business Intelligence Implementation Traditional BI systems use a large volume of static data that have been extracted, cleansed, and loaded into a DW to produce reports and analyses. Users need business monitoring, performance analysis, and an understanding of why things are happening. These can alert users, virtually in real-time, about changes in data or the availability of relevant reports, and so on

Structure and Components of Business Intelligence

Structure and Components of Business Intelligence Data warehouse Data flows from operational systems (e.g., CRM, ERP) to a DW, which is a special database or repository of data that has been prepared to support decision-making applications ranging from those for simple reporting and querying to complex optimization

Structure and Components of Business Intelligence Business analytics Online analytical processing (OLAP) Software tools that allow users to create on-demand reports and queries and to conduct analysis of data

Structure and Components of Business Intelligence Data mining Data mining is a class of database information analysis that looks for hidden patterns in a group of data that can be used to predict future behavior Used to replace or enhance human intelligence by scanning through massive storehouses of data to discover meaningful new correlations, patterns, and trends, by using pattern recognition technologies and advanced statistics

Structure and Components of Business Intelligence Business performance management (BPM) Based on the balanced scorecard methodology—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

Business Intelligence Today and Tomorrow Recent industry analyst reports show that in the coming years, millions of people will use BI visual tools and analytics every day Today’s organizations are deriving more value from BI by extending actionable information to many types of employees, maximizing the use of existing data assets

Business Intelligence Today and Tomorrow A potential trend involving BI is its possible merger with artificial intelligence (AI) BI is spreading its wings to cover small, medium, and large companies BI takes advantage of already developed and installed components of IT technologies, helping companies leverage their current IT investments and use valuable data stored in legacy and transactional systems