...Analytics: Driving Return on Human Capital Investment HR Analytics: Driving Return on Human Capital Investment The Business Need for Improved HR Analytics ................................. 3 Leading Practices for Improved Organizational Performance ............ 4 HR Analytics Contributes by Driving Insights to Action ...................... 5 Addressing Information Needs through Analytic Workflows ........... 5 About Oracle Business Intelligence Applications ............................... 7 The Foundation: OBIEE 11g .......................................................... 8 HR Analytics Subject Areas ........................................................... 9 A Case Story ................................................................................... 15 Benefits and ROI ............................................................................. 17 The Value of a Pre-Built Solution ................................................. 17 Business Value Adds Up ............................................................. 17 Maximizing Success – Next Steps ................................................... 19 Conclusion ...................................................................................... 20 The Business Need for Improved HR Analytics As worldwide economic and political conditions continue to concern business leaders, their attention turns to the various levers that can foster success in uncertain times. Employee salaries make up...
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...Know how Managing knowledge for competitive advantage An Economist Intelligence Unit white paper sponsored by Tata Consultancy Services Know how Managing knowledge for competitive advantage Acknowledgements Know how: Managing knowledge for competitive advantage is a briefing paper written by the Economist Intelligence Unit and sponsored by Tata Consultancy Services (TCS). The findings and views expressed in this white paper do not necessarily reflect the views of TCS, which has sponsored this publication in the interest of promoting informed debate. The Economist Intelligence Unit bears sole responsibility for the content of the report. The main author was Terry Ernest-Jones and the editor was Gareth Lofthouse. The findings are based on two main strands of research: ● The Economist Intelligence Unit conducted an online survey of 122 senior executives in western Europe, 68 of whom were based in the UK. Participants were selected from large organisations with over $1bn in annual sales revenue, and from a cross-section of industries, with a particular emphasis on financial services, healthcare and pharmaceuticals, telecommunications and professional services companies. ● We also interviewed several senior executives and knowledge-management practitioners on the challenges they face in managing corporate knowledge, and on the strategies they have employed to exploit business information for competitive advantage. Our sincere thanks go to all the interviewees and survey...
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...Major risks of using BI Deploying BI using conventional methods exposes a company to considerable risk due to the time involved in implementing BI, and the technical resources needed for deployment (Zap). The average business intelligence solution costs $1.8 million and takes more than 2 years to implement (Rosen). BI systems needs to be designed to suit the business goals not start with using technology and try to suit it to the business goals. The BI system also needs to be easily adapted to any new business logic that might be adopted in the future as the business changes. The biggest risk of BI is the time taken to develop the BI solution. It can take months to develop a solution that is tailored for the business, also the ongoing maintenance can require deep technical expertise and a lot of time. To evaluate the back end of a BI solution there are a few things that need to be addressed. This includes how quickly the data structure can be developed to deliver a BI solution across all subject areas in your system. This is important in the decision of BI as the time represents the cost of developing the solution. The depth of technical skills required to deploy the solution is also important because the greater the skills needed the more the solution will cost. It also needs to be determined how much technical expertise will be needed to maintain the system and to make future modifications to keep to system up to date. This is an important factor because the amount of expertise...
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...massive volume of data. It's usually so massive that it becomes complicated to comprehend using tools such as on-hand database, and traditional data processing applications. Some problems that come up are storage, sharing, analysis, and search.Even though these problems do occur it still can be helpful in business operations, and better business decisions. This data can also help give companies informations which can increase profit, bring more customers, and overall increase the business's value. Characteristics of Big Data include the five V’s. The first one is volume, which is the quantity of data. The second is Variety, which the type of Data. The third is velocity, which is the speed of the data is gathered. The fourth one Variability, which is inconsistency of data can hamper processes to manage it. The final one is Veracity, which is the quality of data captured can vary. These data sets are growing rapidly mainly because they are gathered at a fairly cheap. The world's technological per-capita are doubling every 40 months. Business intelligence with data with high information density to look for trends. Big Data also increased information management specialist. Some of the largest companies like IBM and Microsoft spent over 15 billion dollars on software firms which specialize in data analytics. Governments use big data because it's efficient in terms of productivity and innovation. While gathering big data is a big benefit there are also some issues that need...
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...Business intelligence software, the software of the future Abstract This report offers insight on business intelligence software and how it can be used to help a company run more effectively. Specifically the report analyzes 4 questions: how do organizations benefit from Business Intelligence solutions, how can dashboards help the average user, what role does Business Intelligence play in competitive advantage and organizational strategy, and how can “Big Data” and Business Intelligence work together? A comparison of Cognos and Tableau business software is made to help explain how different software works and guide you toward picking the correct software for you. Also included is a summary of case study performed on a company that implemented a BI solution. After reading this report, the audience should have a better understanding of how and why business intelligence software is implemented. Companies everywhere are always looking for solutions to make their business work more efficiently. In the last 10 years, a number of companies have been investing in software that will provide a better understanding of metrics to foretell their future performance. This same software can help companies make the most of their resources by turning stacks of data into stacks of opportunity. Knowing which software is most effective for specific business solutions can help you in choosing the best business intelligence software. The purpose of this report is to compare...
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...Jacob Moore GBA 673 Business Intelligence Jacob Moore GBA 673 Dr. Lara Preiser-Houy, CDP August 20th, 2013 1|Page Jacob Moore GBA 673 Table of Contents Abstract ....................................................................................................................................................... 3 Introduction ............................................................................................................................................... 3 Background ................................................................................................................................................ 4 Conceptualization ..................................................................................................................................... 4 BI 1.0 ......................................................................................................................................................... 4 BI 2.0 ......................................................................................................................................................... 5 BI 3.0 ......................................................................................................................................................... 5 Opportunities ............................................................................................................................................ 6 Challenges ........................................
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...Communications of the Association for Information Systems (Volume13, 2004) 177-195 177 BUSINESS INTELLIGENCE Solomon Negash Computer Science and Information Systems Department Kennesaw State University snegash@kennesaw.edu ABSTRACT Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the timeliness and quality of inputs to the decision process. Business Intelligence is used to understand the capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes; and the actions of competitors and the implications of these actions. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously. Although business intelligence systems are widely used in industry, research about them is limited. This paper, in addition to being a tutorial, proposes a BI framework and potential research topics. The framework highlights the importance of unstructured data and discusses the need to develop BI tools for its acquisition, integration, cleanup, search, analysis, and delivery. In addition, this paper explores a matrix for BI data types (structured...
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...Differences between AQL and OLAP Auteur Peter den Heijer Adres Veldhofstraat 16 Postcode 7213 AM Plaatsnaam Gorssel Emailadres pdheijer@gmail.com Telefoonnummer 0575-490719 Datum 26 mei 2012 Opleidingsinstituut CAI Opleiding Business Intelligence Opleidingscode BUSI1201UTRx Docent Emiel Caron Versie 3.0 Pagina 1 van 19 Inhoud 1. Introduction ..................................................................................................................................... 3 2. Business Case................................................................................................................................... 3 3. Central Research Question .............................................................................................................. 3 4. Purpose............................................................................................................................................ 3 5. Sub Questions.................................................................................................................................. 4 6. Research Methodology and Scope .................................................................................................. 4 7. Introduction Qlikview ...................................................................................................................... 4 8. Definition of OLAP...
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...Week 1 Assignment - POPULAR BUSINESS JOURNALS to: | | from: | | subject: | SUCCESSFUL BI IMplEMENTATIONS – INSURANCE INDUSTRY | date: | January 11, 2015 | | | | | Over the past decade due to increased competition, product commoditization and price pressure, insurance companies are seeking to create differentiated value propositions in their products, while reducing losses and improving efficiencies. Business people in functions such as sales, marketing, finance, underwriting, and claims all drive the bottom line. Profitability depends on ensuring everyone in the insurance company makes optimal decisions. Three such leading insurers that applied Business Intelligence solutions successfully to acquire the aforementioned are below. EMC Insurance Companies struggled with pinpointing the right amount of money to hold in reserve against potential case payouts; holding back either too much or too little could be disadvantageous to the firm’s bottom line. The company selected PolyVista, advanced data analytics software built on Microsoft SQL Server Analysis Services, to uncover anomalies, correlations, relationships, and patterns hidden within the firm’s warehouse of claim data. After deploying the solution, EMC was able to improve financial reserve management, identify claims requiring special attention, improve data quality, support executive decision making with improved analysis, and better manage expenses. GEICO uses MicroStrategy to analyze over 20 terabytes of customer...
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...Communications of the Association for Information Systems (Volume13, 2004) 177-195 177 Business Intelligence by S. Negash BUSINESS INTELLIGENCE Solomon Negash Computer Science and Information Systems Department Kennesaw State University snegash@kennesaw.edu ABSTRACT Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the timeliness and quality of inputs to the decision process. Business Intelligence is used to understand the capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes; and the actions of competitors and the implications of these actions. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously. Although business intelligence systems are widely used in industry, research about them is limited. This paper, in addition to being a tutorial, proposes a BI framework and potential research topics. The framework highlights the importance of unstructured data and discusses the need to develop BI tools for its acquisition, integration, cleanup, search, analysis, and delivery. In addition, this paper...
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...Communications of the Association for Information Systems (Volume13, 2004) 177-195 177 BUSINESS INTELLIGENCE Solomon Negash Computer Science and Information Systems Department Kennesaw State University snegash@kennesaw.edu ABSTRACT Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the timeliness and quality of inputs to the decision process. Business Intelligence is used to understand the capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes; and the actions of competitors and the implications of these actions. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously. Although business intelligence systems are widely used in industry, research about them is limited. This paper, in addition to being a tutorial, proposes a BI framework and potential research topics. The framework highlights the importance of unstructured data and discusses the need to develop BI tools for its acquisition, integration, cleanup, search, analysis, and delivery. In addition, this paper explores a matrix for BI data types (structured...
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...Interdisciplinary Journal of Information, Knowledge, and Management Volume 2, 2007 Approach to Building and Implementing Business Intelligence Systems Celina M. Olszak and Ewa Ziemba University of Economics, Katowice, Poland olszak@ae.katowice.pl ewa.ziemba@ae.katowice.pl Abstract Abstract: The article aims at describing processes of building Business Intelligence (BI) systems. Taking the BI systems specifics into consideration, the authors present a suggested methodology of the systems creation and implementation in organisations. The considerations are focused on objectives and functional areas of the BI in organisations. Hence, in this context the approach to be used while building and implementing the BI involves two major stages that are of interactive nature, i.e. BI creation and BI “consumption”. A large part of the article is devoted to presenting objectives and tasks that are realised while building and implementing BI. Key words: Business Intelligence, methodology of BI construction, designing BI, business decision-making, knowledge management Introduction Socio-economic reality of contemporary organisations has made organisations face some necessity to look for instruments that would facilitate effective acquiring, processing and analysing vast amounts of data that come from different and dispersed sources and that would serve as some basis for discovering new knowledge. For long time management information systems (MIS) have been supporting organisations in their...
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...Chapter 12 Business Intelligence and Decision Support Systems Goals of the Chapter The primary objective of this chapter is to recognize the importance of data, the management issues that relate to it, and its life cycle. Other objectives include relating data management to multimedia and document management, explaining the concept of data warehousing, data mining, analytical processing, and knowledge discovery management. An Overview Section 12.1 – The Need for Business Intelligence – The section serves as an overview of Business Intelligence and its use in business. It discusses the problems associated with disparate data stores where data are not integrated into a single reporting system. The section discusses the technologies involved in Business Intelligence and the vendors involved. It also talks about predictive analytics, alerts and decision support. Section 12.2 – BI Architecture, Reporting and Performance Management – This section discusses the modes of data extraction and integration into a standardized, usable and trustworthy one. It also discusses the different types of reporting systems available to organizations, data mining, query and analysis. The section provides an insight into Business Performance Management (BPM) as a way for business managers to know if their organizations are achieving their strategic goals Section 12.3 – Data, Text and Web Mining and BI Search – This section discusses data mining technology, tools, and techniques. Information types...
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...REPORT FIRST QUARTER 2007 PREDICTIVE ANALYTICS Extending the Value of Your Data Warehousing Investment By Wayne W. Eckerson Research Sponsors MicroStrategy, Inc. OutlookSoft Corporation SAS SPSS Sybase, Inc. Teradata, a division of NCR www.tdwi.org PREDICTIVE ANALYTICS Extending the Value of Your Data Warehousing Investment By Wayne W. Eckerson Table of Contents Research Methodology and Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 What Is Predictive Analytics? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 The Business Value of Predictive Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Measuring Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 How Do You Deliver Predictive Analytics? . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 11 The Process of Predictive Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1. Defining the Project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2. Exploring the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3. Preparing the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
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...Course Related 2 Virtual Expert 2 JSB Inc. 2 James S. Black (Company founder) 2 Abigail Foley (Senior vice president of Business Development) 2 Mark Thompson (Business Development Manager) 2 Major Business Functions (In JSB) 3 Manufacturing 3 Sales and Marketing 3 Human Resources 3 Finance and Accounting 3 Terms 3 Information vs Data 3 Digital Manufacturing 3 DELMIA 3 POS 3 Inventory Management System 3 Mapping Technology 3 Electronic Business / E-Business 3 Electronic Commerce / E-Commerce 3 E-Government 3 Problem Solving 3 Critical Thinking 3 Steps 3 1. Problem Identification 3 Dimensions of Business Problems 3 Organizations 3 Technology 3 People 3 Examples 3 2. Solution Design 3 3. Solution Evaluation and Choice 3 4. Implementation 3 Analyzing Performance 3 Case Study Analysis 3 Identify the most important facts surrounding the case 3 Identify key issues and problems 3 Specify alternative courses of action 3 Evaluate each course of action 3 Recommend the best course of action 3 Information Systems 3 Definition 3 Information Technology versus Information Systems 3 Information Technology 3 Information System 3 Dimensions 3 Organization 4 Technology 4 Components 4 Hardware 4 Software 4 Data Management Technology 4 Networking and Telecommunications Technology 4 Function 4 People 4 Functions 4 Input 4 Processing 4 Output 4 Types 4 Strategic-level systems 5 ...
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