...Statistical Databases Jaideep Srivastava and Hung Q. Ngo, Department of Computer Science, University of Minnesota, 200 Union street, EE/CS Building, room 4-192, Minneapolis, MN 55455 e-mail: srivasta, hngo @cs.umn.edu, ¡ 1 Introduction A statistical database management system (SDBMS) is a database management system that can model, store and manipulate data in a manner well suited to the needs of users who want to perform statistical analyses on the data. Statistical databases have some special characteristics and requirements that are not supported by existing commercial database management systems. For example, while basic aggregation operations like SUM and AVG are part of SQL, there is no support for other commonly used operations like variance and co-variance. Such computations, as well as more advanced ones like regression and principal component analysis, are usually performed using statistical packages and libraries, such as SAS [1] and SPSS [2]. From the end user’s perspective, whether the statistical calculations are being performed in the database or in a statistical package can be quite transparent, especially from a functionality viewpoint. However, once the datasets to be analyzed grow beyond a certain size, the statistical package approach becomes infeasible, either due to its inability to handle large volumes of data, or the unacceptable computation times which make interactive analysis impossible. With the increasing sophistication of data collection instrumentation...
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...Fine Foods While developing the Kudler Fine Foods marketing campaign strategy it is critical to identify areas which will need additional marketing research. By identifying areas for needed additional market research, Kudler Fine Foods can better target its marketing strategy and tactics. By analyzing competitive intelligence, Kudler Fine Foods can better assess opportunities within its current marketing strategy. Background Kudler Fine Foods was founded in 1998 when its first store was built by Kathy Kudler. The company maintains its main base in San Diego, California and services the neighborhoods of La Jolla, Del Mar, and Encinitas. Each store has more than 16,000ft of modernized groceries and fresh organic specialty foods. Kudler Fine Foods prides itself on offering high quality foods, both domestic and imported. The company maintains specific strategic practices to introduce planning unrealistic goals and objectives. Although the company services a niche market in a minimal geographic area, the grocery industry is inherently competitive. The success of the company is attributed to its high standards in human resources and inventory control. By identifying additional areas for marketing research and analyzing competitive intelligence, Kudler Fine Foods will be able to expand its operations and establish more locations. The company is currently interested in further developing its strategic goals for increased...
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...economy is the focus of this paper, specifically in the financial services environment. The steps in the implementation of CRM as proposed by Peppers, Rogers and Dorf (1999b) are examined and the effect on customer service in an emerging market is investigated. The findings indicate that there are positive associations with these steps and customer service. INTRODUCTION Changes in customer expectations can be identified throughout the world. Customer relationship management (CRM) strategies have become increasingly important worldwide due to these changes in expectations from customers as well as changes in the nature of markets. Changes have been noted across the world, but opportunities present themselves in South Africa and other developing countries for CRM strategies. Customer Relationship Management (CRM) is a managerial philosophy that seeks to build long term relationships with customers. CRM can be defined as “the development and maintenance of mutually beneficial long-term relationships with strategically significant customers” (Buttle, 2000). Under certain circumstances it may result in the termination of relationships (du Plessis, Jooste & Strydom, 2001). It can also Adele Berndt is currently an Associate Professor in Marketing at the University of Johannesburg. Her areas of specialisation...
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...translation engines. For this purpose we have used the method of hybrid machine translation. Hybrid machine translation is a method of machine translation that is characterized by the use of multiple machine translation approaches within a single machine translation system. The motivation for developing hybrid machine translation systems stems from the failure of any single technique to achieve a satisfactory level of accuracy. B. Statistical Machine Translation Statistical Machine Translation systems make use of computer algorithms that find out many possible ways of connecting smaller pieces of text together, in order to produce a best translation. Statistical Machine translation basically translates words and phrases along with their statistical likelihood. These are learned automatically from previously translated text, creating a bilingual “database” of translations. A program referred as decoder matches the source code and phrases with the translation databases and searches for all possible translation combinations. An algorithm is then used to select the best translation out of the millions of possible translations and output it. The main advantage of statistical systems is the high levels...
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...1. Understand the importance of determining information system requirements for all management levels by developing an understanding of the differences between various types of information systems 2. Understand how information systems are developed 3. Understand the computer revolution and its impact on the way business is conducted 4. Become familiar with critical-thinking skills in identifying information systems problems and how to investigate existing literature about hardware and software solutions to problems. 5. Know the components and functions of computer systems, both hardware and software. 6. Become familiar with the advances in networking, data communications and the Internet and how they affect the way business is conducted. 7. Identify which information technology tools are used to solve various business problems. 8. Develop proficiency solving business problems using modern productivity tools (e.g., spreadsheet, database) or creating custom programs. MIS 301: Statistical Analysis for Business At the end of this course students should be able to: 1. Use data from a sample to make inferences about a population. 2. Apply probability theory in decision making situations. 3. Formulate hypotheses for decision making and research. 4. Analyze data using appropriate statistical techniques. 5. Interpret the results of statistical analysis. 6. Present statistical results using graphics, text, and the spoken word. MIS 302: Introduction to Operations Management At the...
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...Big Data and its Effects on Society Kayla Seifert MGT-311 November 23, 2015 Big Data is a concept that has existed for a while but only gained proper attention a couple of years ago. One can describe Big Data as extremely large data sets that have grown so big that it becomes almost impossible to manage and analyze with traditional data processing tools. Enterprises can use Big Data by building new applications, improving the effectiveness, lowering the costs of their applications, helping with competitive advantage, and increasing customer loyalty. It can also be used in other industries to enable a better system and better decision-making. Big Data has become a valuable asset to everyone around the world and continues to impact society today. The ideology of Big Data first came up in the days before the age of computers, when unstructured data were the norm and analytics was in its infancy. The first Big Data challenge came in the form of the 1880 U.S. census when the information involving about 50 million people being gathered, classified, and reported. This census contained a lot of facts to deal with, however, limited technology was available to organize and manage it. It took over seven years to manually put the data into tables and report on the data. Thanks to Big Data, the 1890 census could be placed on punch cards that could hold about 80 variables. Instead of seven years, the analysis of the data only took six weeks. Big Data allowed the government...
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...Jithin Ram Nambiar | Wrkfrc/Wrkgrp | Solns/Tech Slns | Metro City | Chennai | Standard Job | | Level | Senior Programmer | Office Location | Chennai 1 - Tek Meadows | Bill Code | 30 | MAL < 12 | Y | Geo Unit | India | Talent Fulfillment Specialist | TBD | | | | | | | Hire Date | November 30, 2011 | | | People Advisor | Gunjan Priya | | Individual Deployed to Entity | Technology > Delivery > GDN for Technology > APAC Delivery Centers > India Delivery Center > H&PS > HPS-HC > Others > HPS-HC-01 | | | | | | | | | | | Specialty | Proficiency | Functional/Technical Specialty | Technical > Packaged Software & Apps > Industry Applications-PRD > Products Industry Applications | Not Assessed | Industry Specialty | Industry > No Industry Specialty | Not Assessed | | | | | | | | | | Office Phone: | Email Address: jithin.ram.nambiar@accenture.com | | | | | | | Profile Summary | | | I hold a B-Tech degree in Electronics and Communication Engineering from Amrita University. I have 42 Months experience in Healthcare IT. Previously worked as an Implementation Consultant with Allscripts and was involved in the implementation and support of the Sunrise Acute care and Ambulatory products. Before joining Allscripts I worked with a Domestic Healthcare Company as Business Analyst and was involved in the implementation of HIS and LIS at various...
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...ability to apply it to huge amounts of data—without compromising performance—generates the competitive edge. Second, Big Analytics refers to the sophistication of the model itself. Increasingly, analysis algorithms are provided directly by database management system (DBMS) vendors. To pull away from the pack, companies must go well beyond what is provided and innovate by using newer, more sophisticated statistical analysis. Revolution Analytics addresses both of these opportunities in Big Analytics while supporting the following objectives for working with Big Data Analytics: 1. 2. 3. 4. Avoid sampling / aggregation; Reduce data movement and replication; Bring the analytics as close as possible to the data and; Optimize computation speed. First, Revolution Analytics delivers optimized statistical algorithms for the three primary data management paradigms being employed to address growing size and increasing variety of organizations’ data, including file-based, MapReduce (e.g. Hadoop) or In-Database Analytics. Second, the company is optimizing algorithms - even complex ones - to work well with Big Data. Open Source R was not built for Big Data Analytics because it is memory-bound. Depending on the type of statistical analysis required, Big Data also causes issues...
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...input into decision making. Classifications of marketing research.: 1) Problem identification research: The goal is to identify existing or potential problems not apparent on the surface. Examples include market potential, market share, market characteristics, sales analysis, short-range forecasting, long-range forecasting, and business trends research. 2) Problem solution research: The goal is to solve specific marketing problems such as segmentation, product, pricing promotion, and distribution research. Steps involved in the marketing research process: 1) Problem definition: Defining the marketing research problem to be addressed is the most important step because all other steps will be based on this definition. 2) Developing an approach to the problem: Development of a broad specification of how the problem will be addressed allows the researcher to break the problem into salient issues and manageable pieces. 3) Research design formulation: A framework for conducting the marketing research project that specifies the procedures necessary for obtaining the required information....
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...25% produced by Turnitin, can only achieve a maximum grade of E. Assignment Title: “Performance Lawn Equipment” Issue date: Week One: Monday 19/10/2015 Submission due date: Week 7: 07/12/2015 Week 9: Friday 08/01/2016: A single report per student should be submitted via the TURNITIN link in the Assessment folder. Assignment must not be e-mailed under any circumstances. Unit co-ordinator’s name: C F Shooshtarian Core learning outcomes | | On completion of this unit you should be able to: | Assessment number | 1 | Investigate and analyse a variety of problems and data sets in the context of different analytics to develop insights in order to support management decision making. | 1 | | | 2 | | | | 2 | Apply statistical and mathematical technique to find solutions to analysis conducted using suitable software. | 1 | | | 2 | | | | Threshold standards | Assessment number | In order to pass the assessment you will need to: |...
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...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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...in marketing. The five steps include Defining the problem, developing the research plan, collecting relevant information, developing findings, and taking marketing actions. Constraints in a decision are the restrictions placed on potential solutions to a problem such as limitations on time and money. The difference between primary and secondary data is that primary data are facts and figures that are newly collected for the project, while secondary data are facts and figures that have previously been recorded. Some advantages of secondary data are the time savings, and the low cost. disadvantages of secondary data include that the secondary data may be out of date and the categories might not be right for the researchers project. The difference between observational and questionnaire data are that observational data can be collected by mechanical, personal, or neuromarketing methods, while questionnaire data are facts and figures that are obtained by asking people. Personal Interview provides the greatest flexibility. The difference between a panel and experiment is that a panel is a sample of consumers or stores from which researches take a series of measurements, while an experiment obtains data by manipulating factors under controlled conditions to test cause and effect. Data mining differs from traditional marketing research because data mining is extracting information about someone through large databases, while traditional marketing research is analyzing information...
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...maintain by government and private agencies as; National Bureau of Economic Research (NBER'S Macro-Historical Database), Bureau of Labor Statistics (BLS), Federal Reserve Economic Data (FRED), and Congressional Budget Office (CBO). In addition, the raw data is use for the purpose of measuring past relationships among variables such as historical data, employment, prices, productivity, population, government budget, and government spending. Thus, resulting in economist anticipating change in some variables; in which will either affect or not affect the future course of the U.S. economy short and long run performance. Primary Sources Therefore, the National Bureau of Economic Research (NBER'S Macro-Historical Database) was founded in 1920 over the years the NBER's research agenda has varied from a wide variety of issues that confront our economic society. Early research focused on the aggregate economy, examining in detail the business cycle and long-term economic growth. Whereby, its known as private, non-profit, non-partisan research organization's main aim is to promote greater understanding of how the economy works. It disseminates unbiased economic research among public policymakers, business professionals and the academic community. Today, some 1,300 academics are NBER researchers, and they focus on "four types of empirical research: developing new statistical measurements, estimating quantitative models of economic behavior, assessing the effects of public policies...
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...software house, or multinational organization in the field of information technology. Aiming to fully utilize my professional experience, academic background, and further develop my technical skills. Work Experience Etisalat Misr – Outsourced by BBI 4/2011-Present Role * System Analyst * System Analyst in Data Quality - DWH Team. * Include service quality measures in the requirement/design for all projects. * Achieve quality assurance for new and modified models. * Increase quality checks for early problems detection by keeping enhance data quality process and methodology. * Grant smooth end month/end year closing for the Finance Department. * Performing daily, weekly, and monthly statistical reports, spreadsheets and graphs that ensure the integrity of trends for vital areas of the telecom operation and KPIs that support in taking right decisions. * Checking usage and revenue trends and investigate the reasons behind any deviations or spikes. * Validate the quality of data extracted against the business rules on daily basis. * Daily follow up on quality issues resolution with other IT teams (IN, Billing, App. Support…). * Fulfill commercial Calendar, BI Reporting requirements and Self Service user requirements. * Act as second line support for issues escalated by the Application support team. Major...
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...Chapter 4 Review Question 1 The process of stating the basic dilemma and then developing other questions by progressively breaking down the original question into more specific ones is called the _____. research question management-research-question hierarchy management dilemma management question investigative question Question 2 Which of the following statements is false regarding the evaluation of alternatives? The selection of alternatives is determined by the decision variable chosen and the decision rule used Each alternative must be explicitly stated A decision variable is defined by an outcome that may be measured A decision rule is determined by which outcomes may be compared all of the above are true Question 3 Apple plans to survey every customer who has purchased an Apple computer in the last 5 years. Apple plans to use a _____. convenience sample snowball sample systematic sample census random sample Question 4 Ensuring consistency among respondents, locating omissions, and reducing errors in recording are all benefits of data collection data editing sampling coding data analysis Question 5 Reducing data to a manageable size, developing summaries, and applying statistical techniques are all aspects of sampling data collection pilot testing data analysis data transformation Question 6 A synopsis of the problem, findings, and recommendations are provided in the ____ section of a research report. executive summary abstract ...
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