...cu MOVEIN BUSINESS INTELLIGENCE AND ANALYTICS REPORT me nt ap A Business Plan on the Role of Business Intelligence and Analytics for MoveIn Pty Ltd Th ink sw Do TABLE OF CONTENTS Executive Summary ........................................................................................................................ 2 1 -‐ Introduction .............................................................................................................................. 3 2 -‐ Role of Business Intelligence ..................................................................................................... 3 2.1 -‐ Business Intelligence -‐ Overview ............................................................................................... 3 2.2 -‐ Business Intelligence Tools ........................................................................................................ 4 2.2.1 -‐ On-‐line Analytical Processing .............................................................................................. 4 2.2.2 -‐ Data Mining ........................................................................................................................ 5 ...
Words: 4854 - Pages: 20
...Business Intelligence-The Next Ruler of IT Monalisa Mishra “In GOD we trust for everything else we need data” -W. Edwards Deming In the present era the old saying has become the buzz of corporate circle and going forward this will be the base principle of decision makers across the world. Welcome to the era of objective thinking powered by technology that has given a new dimension to business and management. With the passage of time more and more companies are coming forward to adopt, improvise and leverage on technology and Business Intelligence has proved to be the flag bearer in this upcoming trend. Business Intelligence, in layman terms, is data converted to information and available in ready to use format that can be further analyzed, modified and transformed as per the changing demand. The industries today are mostly into some or other form of nascent technology that speaks of raw form of information. Basically, these systems are into huge data repository that provides real time information or basics analytic tools that can provide historical analysis. But the future has a lot more to offer. Imagine an automotive plant with fluctuating marketing demand , supply chain constraint and increasing production costs. In such a scenario, we can only expect something beyond human intelligence to give smart solution that approximately optimizes every aspect. Now let us think of a system that is integrated with the production system and marketing technical system. This system...
Words: 1375 - Pages: 6
...Oracle® Business Intelligence Applications Installation Guide for Informatica PowerCenter Users Release 7.9.6.4 E35271-01 November 2012 Provides the steps to install and set up Oracle Business Intelligence Applications Release 7.9.6.4. Oracle Business Intelligence Applications Installation Guide for Informatica PowerCenter Users, Release 7.9.6.4 E35271-01 Copyright © 2009, 2012, Oracle and/or its affiliates. All rights reserved. Primary Author: P Brownbridge This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed...
Words: 60905 - Pages: 244
...Cloud computing and analytics Name: Course: Tutor: Date: 1. Introduction Organizations and individuals collect vast amounts of data in their day to day operations. Data growth comes from multiple sources: From the use of computing within an enterprise for business functions such as commerce, customer service, and resource management. Use of communication devices, including computers, tablets, and mobile phone by individuals for both work and personal use also increases the daily data collected. The instrumentation of physical infrastructure, such as electrical grids, highways, and buildings for more efficient monitoring and management, opens the opportunity to collect a lot of data. It is expected that the trend will continue as both enterprises and individuals find value in access to information and communication. The challenge lies in managing the dynamic nature of the data, keeping the data secure and applying the right analytic technique to use the information most effectively. New advances in computing technologies make it possible for organizations to take full advantage of the vast amount of data they collect. 2. Architecture Design Cloud computing is an umbrella term. It encompasses many types of services. What cloud computing does is take a process anchored to one company, one data center and one facility. It enables businesses to move from working within their own IT bubble and use the cloud to access technologies they need, when they need them, at the scale they...
Words: 1244 - Pages: 5
...benefits for in regards to data mining: predictive analytics to understand the behavior of customers, associations discovery in products sold to customers, web mining to discover business intelligence from web customers, and clustering to find related customer information. To understand the behavior of customers by the use predictive analytics we must first understand what predictive analytics is. “Predictive analytics is the process of dealing with a variety of data and applying various mathematical formulas to discover the best decision for a given situation” (ArticleSnatch, 2011). This gives any business a competitive edge and helps to remove the guess work out of the decision making process therefore helping to find the right solution in a shorter amount of time. In order to find the solution faster there are a seven simple steps that must be worked thru first: what is the problem for the company, searching for multiple data resources, take the patterns that are observed from that data, creating a model that contains the problem and the data, categorize the data and find important factors and in turn creating new variables, build a predictive model by using examples, and authorize this model and put it into action. When these steps are followed through with then it makes it easy for businesses to make speedy decisions using the immense amounts of data that they now have. There are multiple benefits of predictive analytics such as: minimizing risk, a decline in...
Words: 1843 - Pages: 8
...Making Business Intelligence Easy White Paper Mobile Business Intelligence and Analytics Mobile Business Intelligence & Analytics Contents Overview ...................................................................................................................................................... 3 What is Mobile Business Intelligence?......................................................................................................... 4 Who is it for? ................................................................................................................................................ 5 What are the external factors driving Mobile Business Intelligence? ........................................................... 6 What are the internal drivers for Mobile Business Intelligence? .................................................................. 7 What benefits are sought? ........................................................................................................................... 8 What organizational factors are required? ................................................................................................... 9 What technology has to underpin a Mobile Business Intelligence initiative? ............................................. 10 Security is paramount ................................................................................................................................ 11 Yellowfin’s Mobile Business Intelligence platform...
Words: 4299 - Pages: 18
...WEEK--1 1. Business environments and government requirements are becoming more complex. All of the following actions to manage this complexity would be appropriate EXCEPT Select one: a. hiring more sophisticated and computer-savvy managers. b. seeking new ways to avoid government compliance. c. avoiding expensive trial and error to find out what works. d. deploying more sophisticated tools and technique. The correct answer is: seeking new ways to avoid government compliance. 2. In the Magpie Sensing case study, the automated collection of temperature and humidity data on shipped goods helped with various types of analytics. Which of the following is an example of prescriptive analytics? Select one: a. warning of an open shipment seal b. real time reports of the shipment's temperature c. location of the shipment d. optimal temperature setting The correct answer is: optimal temperature setting 3. In the Magpie Sensing case study, the automated collection of temperature and humidity data on shipped goods helped with various types of analytics. Which of the following is an example of predictive analytics? Select one: a. real time reports of the shipment's temperature b. optimal temperature setting c. location of the shipment d. warning of an open shipment seal The correct answer is: warning of an open shipment seal Organizations counter the pressures they experience in their business environments in multiple ways. Which of the following is NOT an...
Words: 1533 - Pages: 7
...Harnessing the power of business intelligence: A proposed use case for small, MEDIUM AND MICRO businesses Introduction The subject matter of this research project is based off of a need to know what tools are available for small businesses who wish to compete with their bigger and more financially equipped counterparts. As someone who has always had a great interest in being an entrepreneur, I believe this is as great a medium as any other to delve into the topic of affordable business intelligence solutions for small businesses. In a recent study of small and medium businesses, it was found that they collect a lot of data but are face with the problem of having too much information and a great majority of them did not know how to make best use of it. In essence, they know the importance of collecting data but do not comprehend how to make sense of the data. (Aggarwal, McCabe, & Aggarwal, 2011) The study went on to show that 25% of the small and medium size businesses that took part in the study reported that one of their biggest challenges is getting better insights into the data they collect. But as Todd R. Weiss so put it, it’s also getting much harder for small businesses to find excuses for why they cannot compete with larger competitors on a regional, national and global scale because of the accessibility of software and services (specifically BI tools) via “the cloud”. (Weiss, 2012) This paper will briefly discuss what business intelligence is; why it is so important;...
Words: 1799 - Pages: 8
...IBM Software Group Business Analytics Cognos Enterprise The right architecture for business intelligence The foundation for effective enterprise BI 2 The right architecture for business intelligence Overview In a fast, interconnecting and complex world, it is no longer enough to decide and act on the basis of limited information or traditional strategic planning cycles. New challenges and opportunities require agility: the ability to quickly assess, reinvent and adjust. Business analytics is helping many organizations achieve this kind of agility. Analytics software brings together business intelligence (BI) capabilities such as reporting, analysis and scorecarding with planning, scenario modeling, real-time monitoring and predictive analytics. It lets you tap into information within your organization and beyond, to connect with key stakeholders and to share insight, align and decide. Analytics-driven organizations not only seize opportunities: they outperform. IBM’s 2010 CFO study (involving more than 1,900 CFOs and senior finance leaders worldwide) showed that analytics-driven organizations had 33 percent more revenue growth and 32 percent more return on capital invested. Investing in analytics is considered a priority for many organizations, but a big question can be the technology platform. Which platforms provide the best foundation for positive business outcomes? What kind of architecture best lends itself to accessible analysis, intuitive collaboration...
Words: 4760 - Pages: 20
...According to www.PredictiveAnalyticsWorld.com, “Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model, which has been trained over your data, learning from the experience of your organization. It continues to say, “Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer's predictive score informs actions to be taken with that customer.” Predictive analytics are used to determine the probable future outcome of an event or the likelihood of a situation occurring. It is the branch of data mining concerned with the prediction of future probabilities and trends. Predictive analytics are used to automatically analyze large amounts of data with different variables; it includes clustering, decision trees, market basket analysis, regression modeling, etc. There are three main benefits of predictive analytics: minimizing risk, identifying fraud, and pursuing new sources of revenue. Being able to predict the risks involved with loan and credit origination, fraudulent insurance claims, and making predictions with regard to promotional offers and coupons are all examples of these benefits. This type of algorithm allows businesses to test all sorts of situations and scenarios it could take years to test in the real world. Investing...
Words: 1691 - Pages: 7
...skills • Involved in Ab Initio Design, Configuration experience in Ab Initio ETL, • Data Mapping, Transformation and Loading in complex and high-volume Environment and data processing at Terabytes level. • Capacity of designing solutions around Ab Initio, with advanced skills in high performance and parallelism in Ab Initio • Data warehousing implementation experience • Knowledge of Oracle 8i/9i • Strong analytical & problem solving skills • Strong UNIX, korn shell scripting experience. • Experience in leading a team of ETL developers • Experience in co-coordinating with offshore on development/ maintenance projects Work Location Bangalore, Chennai, Pune Requirement Cognos Lead/ Architect Experience 5-10years Qualification B.E/B. Tech/MCA/ME/M. Tech Candidate Requirement • Extensive Experience & Expertise on Business Intelligence, DW • Min. 3 years of hands on experience with Cognos toolsets, Cognos architecture. • Must have hands on experience on Cognos Report Studio , Cognos Analysis Studio , Metrics Studio , and Cognos 8 portals • Must have experience in building large data warehousing and BI applications. Able to gather requirements, and the ability to lead. Design, Develop, configure and optimize Cognos reports, cubes and dashboards. Have an understanding of logical and physical database design / modeling. Experience with dimensional modeling is a must. Hands on experience to working with SQL...
Words: 1964 - Pages: 8
...IS5111:Integration of IS & Business Business Intelligence and Analytics Abhishek Kumar Singh Anbarasan Thangapalam R Deepak Chattani Naadiya Danapal Ram Vibhakar S [A0120022] [A0119959] [A0119975] [A0119961] [A0120054] A Case study on Business Intelligent and Analytics Systems in NTUC FairPrice Table of Contents Executive Summary ............................................................................................................................. 3 Acknowledgments ............................................................................................................................... 4 1. Introduction ...................................................................................................................................... 5 2. Business Intelligence in Retail Industry: ................................................................................. 6 3. Combining BI in CRM ...................................................................................................................... 7 3.1 Analytical CRM ..........................
Words: 6362 - Pages: 26
...1.0 Introduction Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. It describes the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics is used by companies committed to data-driven decision making. It focuses on developing new insights and understanding of business performance based on data and statistical methods. BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Business analytics makes extensive use of statistical analysis, including explanatory and predictive modeling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions. Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making. Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration...
Words: 4604 - Pages: 19
...SPECIAL ISSUE: BUSINESS INTELLIGENCE RESEARCH BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework. Keywords:...
Words: 16335 - Pages: 66
...SPECIAL ISSUE: BUSINESS INTELLIGENCE RESEARCH BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research...
Words: 16335 - Pages: 66
