...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...
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...WHITE P APER Big Data: Trends, Strategies, and S AP Technology Sponsored by: SAP Carl W. Olofson August 2012 Dan Vesset THE DAWN OF THE INTE LLIGENT ECONOMY The intelligent economy has arrived. The convergence of intelligent devices, social networking, pervasive broadband communications, and analytics is redefining relationships among producers, distributors, and consumers of goods and services. The growth in volume, variety, and velocity of data has created new challenges and opportunities. The information access, analysis, and management challenges of the intelligent economy can overwhelm organizations unprepared for the emerging changes. In this environment, it is not only access to data but the ability to analyze and act upon it that creates competitive advantage in commercial transactions, enables sustainable and secure management of communities, and promotes appropriate distribution of social, healthcare, and educational services. It is not only access to data but the ability to analyze and act upon it that creates competitive advantage. www.idc.com P.508.872.8200 F.508.935.4015 In This White Paper This IDC white paper discusses the emerging technologies of the Big Data movement. It breaks out these technologies according to their most effective roles and use cases. It also discusses why Big Data has become so important at this time and how Big Data can help enterprises reach their business goals. It considers the challenges created by Big Data and how they can...
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...An Organisation And Linkage To Bi 11 4.3.1 The Corporate Level Strategy 11 4.3.2 Business-Level Strategy 12 4.3.4 Operational Strategy 13 4.3.5 Bi implementation strategies 14 4.3.5 Balance Scorecard (BSC) 15 5. The Macro Environment of Sensible Solution Ltd 17 5.1 Swot Analysis 17 5.2 Pestle Analysis 18 6. CONCLUSION/RECOMMENDATIONS 19 7. REFERENCES 21 LIST OF FIGURES Figure 1:Linking Sensible Solution Ltd strategy and goals with Business Intelligence 5 Figure 2:Linkage in Organisation & Functional Benefits of Business Intelligence 6 Figure 3:What business intelligence means in practice 7 Figure 4:The Road Map of BPM define the steps that the company needs to follow as a guide to ensure that the I.T Strategic has the same goals as business strategy 9 Figure 5:ERP integration of all departments within organisation 10 Figure 6:The Enterprise Data Model is the Foundation for Linking Strategy and Analytic Capabilities - it Links the Data to the Business Strategy 11 Figure 7:Business Strategy and BI capabilities 12 Figure 8:The layout of Corporate Strategy, Business Strategy and Operational strategy Links to BI 13 Figure 9:The BI Pathway Methods 14 Figure 10:Business intelligence development process flow from requirements through implementation. 15 Figure 11: The logic of the balanced scorecard 16 Figure 12: SWOT analysis 17 Figure 13 :PESTLE Analysis of Sensible Solution 18 LIST OF APPENDIX APPENDIX A APPENDIX B 1. EXECUTIVE SUMMARY ...
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...on Business Decision Making ( Prity) INTRODUCTION Because of the globalization everyone can do business wherever find profitable place or location, for technological development it become easier and accessible to do business one corner from another corner of the world. Although there is lots or benefits for technological advancement, for operating every business in every place there are some problem also. So for effective business organization should plan for their project. For market research, Abacus Research and Analytics (ARA) a research institute, this institute is going to do a research on consumer behaviors and attitudes towards Food Discount in Retailing by Wm Morrison in Greater London for providing the customer better services. This research will help the organization to take correct and concrete decision for the improvement of customer service for customer satisfaction. Amicus company ltd., Royal company ltd., and . Every company has some problem to operate business although these companies located in good places. These companies want to acquire customer satisfaction by improving customer services. So for better improvement in customer services, Abacus Research and Analytics (ARA) is doing a research for taking correct decision. Abacus Research and Analytics (ARA) collect their information from primary and secondary sources which are authentic as well as accurate, and necessary tools which are relevant to this research used to analysis and calculating data for...
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...Research paper Business Intelligence in the Market By Bryan Bock Dr. Traci O'Neill Business Marketing Montana Tech of The University of Montana December, 13 2012 Abstract Businesses today are working more towards predicting the future, how employees will connect with customers, any way or trend the business can find to improve sales and profit. Business Intelligence is used in the market all around the world in many different areas. Businesses are benefitted from the different types of BI methods all the time. Two of the BI methods that are beneficial are called the Market Basket Analysis (MBA) and the Decision Tree Analysis. These two BI methods are used throughout businesses in areas such as marketing, financing, Real estate, and accounting. Both of these methods help business similarly, but in their own different ways. They are two different types of methods that both help businesses make the best decisions to benefit their company. There are many methods or theories that people come up with to help with a business but these are the few that will be examined in this paper. The goal of the modeling technique market basket analysis is to find different relationships of activities that have been recorded with data through the performance of people. This method can be used on any situation where information can be recorded and identified (Pillai, 2011). The way to improve methods for...
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...Business Intelligence as an indispensable tool for decision making in big companies * What is Business intelligence exactly? (Bapt ou Greg) Business intelligence, or BI for short, is a term that refers to competencies, processes, technologies, applications and practices used to support evidence-based decision making in organisations. In the widest sense it can be defined as a collection of approaches for gathering, storing, analysing and providing access to data that helps users to gain insights and make better fact-based business decisions. The basic components of Business Intelligence are gathering, storing, analysing and providing access to data (see Figure). Gathering Data Gathering data is concerned with collecting or accessing data which can then be used to inform decision making. Gathering data can come in many formats and basically refers to the automated measurement and collection of performance data. For example, these can come from transactional systems that keep logs of past transactions, point-of-sale systems, web site software, production systems that measure and track quality, etc. A major challenge of gathering data is making sure that the relevant data is collected in the right way at the right time. If the data quality is not controlled at the data gathering stage then it can jeopardise the entire BI efforts that might follow - always remember the old adage - garbage in garbage out. Storing Data Storing Data is concerned with making sure the data...
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...CSCI 1507 (1903) "Enterprise level data work flows and Data Warehousing" Professor Rajni Palikhey University of Northern Virginia Acknowledgement This Research Paper would not have been possible without the guidance and the help of my co-students and respected Professor who in one way or the other contributed and extended their valuable assistance in the preparation and completion of this research paper. I would to like to convey my sense of gratitude to Professor.Rajni Palikhey who helped and supported us right throughout the semester. This paper would not have been possible without her cooperation and technical assistance. We would also thank our Institution and our faculty members without whom this project would have been a distant reality. We also extend our heartfelt thanks to our family and well wishers. I would like to take this occasion to specially thank University of Northern Virginia to provide us with excellent faculty and also in supporting us getting quality education remotely. Contents SL No Title Page no 1 Abstract 5 2 Introduction to Databases 6 3 OLTP and OLAP Systems 7 4 Difference between OLTP and OLAP 9 5 Data Modeling 13 6 Workflows in Enterprise level Data warehousing 18 7 Business Intelligence tools used in Data flow and Data Warehousing 21 8 Analysis in Data warehousing 24 9 Conclusion 28 10 Foot Note 30 11 References 31 ABSTRACT These days majority...
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...includes the importance of accounting for an effective managerial decision making. It is true that accounting information provides important financial data of company’s costs and revenues; additionally, it also defines options for managers to take decisions on the best option for their companies to minimize cost while increasing profits. The decision making may involve whether to accept special order, make or buy, sell or process further, retain or replace equipment to name a few (Kimmel, Weygandt & Kieso, 2011). This paper discusses the option of incremental and comprehensive analysis and how it can be beneficial to decision making for managers. Furthermore, it elaborates on whether “Incremental analysis is considered to be more economical than a comprehensive analysis, while being just as effective or not” (Learning Assignment, week 6). Incremental Analysis The management usually faces two different types of decisions: a short-term, regarding the normal operation of the company, and long-term capital investments. The short-term decisions can be carried out and then make them retroactive actions to carry out the strategic company goals. In the long-term decision-making, many resources are involved and may include rigid and difficult processes. The short-term decisions may affect different areas that make up an organization, such as sales, finance, production, human resources, etc. There is a wide range of decisions which can be compromised the company's short term and that...
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...Big data is nothing but the collection of large set data which cannot be examined with the normal conventional methods. Big data plays a huge role in different types of industries to improve their business efficiently and effectively. The role of big data is much more in business because many business takes decision based on the data. The workers collects the data relevant to the decisions making. For example, data analyst can track the customer transaction data and helps them to know what kind of improvements can make for increasing their sales. Big data analysis benefits the business to improve the productivity and run efficiently. Basically, leaders depends on the intuition for making the critical decisions but the fact says when leaders uses the data and facts for taking the critical decisions they have the high chance of success. Even though intuition decision making is simple and fast, data based decision are more tactical and by using the modernized technology it is easy for the leaders to finish up the simple tasks and decisions. To incorporate the data into the decision making, leaders must lead in front by supporting the cultural change and by acknowledging the importance of data based decision making and then leaders have to guide their team to get used to the big data analysis. When I was working in electronic based company in India, I had no idea about the big data analysis. The productivity and sales of the company went down at that time. As an employee, I gave...
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...probability concepts to business decisions. Students learn important criterion for developing effective research questions, including the creation of appropriate sampling populations and instruments. Other topics include descriptive statistics, probability concepts, confidence intervals, sampling designs, data collection, and data analysis – including parametric and nonparametric tests of hypothesis and regression analysis. Cooper, D.R., & Schindler, P.S. (2006). Business research methods (9th ed.). Boston, MA: McGraw-Hill/Irwin. Lind, D. A., Marchal, W. G., & Wathen, S. A. (2008). Statistical techniques in business and economics (13th ed.). Boston, MA: McGraw-Hill/Irwin. All electronic materials are available on the student website. |Week One: Descriptive Statistics and Probability Distributions | | |Details |Due |Points | |Objectives |Compute descriptive statistics for given data sets. | | | | |Apply probability concepts related to discrete and continuous probability. | | | |Readings |Read Ch. 3, 5, 6, & 7 of Statistical Techniques in Business & Economics. ...
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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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...MSc. Information System Management Kyaw Khine Soe (3026039) Data Mining and Business Analytics Boston Housing Dataset Analysis. Table of Contents Introduction 3 Problem Statement 3 The associated data of Boston 5 Data pre-processing / Data preparation 8 Clustering Analysis 11 Cluster segment profile 17 Regression Analysis 18 Predictive analysis using neural network node 19 Decision tree node 21 Regression node analysis 23 Model Comparison 24 The recommendation and conclusion 26 Bibliography 27 Introduction This report included part of assignment for the Data Mining and Business Analytics. This report based on the Boston Housing Dataset to describe prediction, cluster analysis, neural networks and decision tree nodes. Boston Housing is a real estate related dataset from Boston Massachusetts. This is small dataset with 506 rows can show prediction of housing price and regressing using decision trees and neural networks over this dataset. This report shows analysis of the property price over the size, age of property, environment factor such as crime rate, near the river dummy, distanced to employment centers and pollution. Problem Statement In relation to housing intelligence, real estate are usually concerned with following common business concerns: 1. Which area are high rates of crime? How crimes rates effected on housing price? How can reduce the crime? 2. Which area is most/lease house price base on rooms in house/ area and...
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...LOGISTICS ALEXANDRIA, EGYPT IMPLEMENTING BUSINESS INTELLIGENCE SYSTEM IN ALEXANDRIA PORT AUTHORITY A Thesis Submitted in Partial Fulfillment of the Requirements for The Degree of Master in International Transport and Logistics By Mahmoud Aly Supervised by Prof. Dr. Mohamed ElFayumy January 2013 Abstract Ports of Alexandria, Damietta and Adabia has already developed and implemented operation control and monitor system that can handle Vessel Movement, Cargo Charge/discharge for both General Cargo and Container terminals , also a warehouse system, Gate control system, and Billing Invoice System, all these steps are the very first steps toward Monitor and control Day to day operation Jobs and tasks in ports, but it doesn’t make a big significance in boosting port performance , in order to take full advantages of these IT systems port authorities should implement Business Intelligence System as BI or EIS “Executive Information System” Combine Operation Data from all different department systems then calculate and analysis these Data into performance report , benchmarks, interactive dashboards showing High port management Executives where and when the performance boost or fail, in a another word BI is acting as Information Technology intended to be as Decision Support System for Executives to take the right decision at the right time saving a lot of cost and redirect wasted effort...
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...| Syllabus School of Business QNT/TM561 Version 2 Research and Statistics for Process Control | Copyright Copyright © 2009, 2005 by University of Phoenix. All rights reserved. University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries. Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation. Edited in accordance with University of Phoenix® editorial standards and practices. Course Description This course prepares graduate students to apply statistics and probability concepts to business decisions in organizations that focus on process improvement. Students learn criteria for developing effective research questions, including the creation of appropriate sampling populations and instruments. Other topics include descriptive statistics, probability concepts, confidence intervals, sampling designs, data collection, and data analysis—including parametric and nonparametric tests of hypothesis and regression analysis. Policies Students/learners will be held responsible for understanding and adhering...
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... | |1.1 Problem definition and background to the problem |2 | |1.2 Scope and limitations of the report |2 | |1.3 The research question |3 | |1.4 A description of the rest of the report |3 | |1.5 Methodology |3 | |2. Findings derived from the Data Analysis | |2.1 Results pertaining to the employer |4 | |2.2 Results pertaining to the employee |12 | |3. Limitations And Conclusions |18 |...
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