Module code: BSS002-6 Module Name: Business Data Analysis Submission: 30 November‚ 2012 I my class I learn how to simulate data to solve a problem. I learn to use excel and some function in it these are =SUM() = RAND() =AVERAGE() =STDV() =RANDINV() =VLOOKUP() and few more . These are widely used function when I simulated data in excel. In task 1 I find out how to calculate or forecast how much card should we print. I use a random variable with =RAND( function and use
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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Turning data into information © Copyright IBM Corporation 2007 Course materials may not be reproduced in whole or in part without the prior written permission of IBM. 4.0.3 Unit objectives After completing this unit‚ you should be able to: Explain how Business and Data is correlated Discuss the concept of turning data into information Describe the relationships between DW‚ BI‚ and Data Insight Identify the components of a DW architecture Summarize the Insight requirements and goals of
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CHAPTER 17 DATA MODELING AND DATABASE DESIGN SUGGESTED ANSWERS TO DISCUSSION QUESTIONS 17.1 Why is it not necessary to model activities such as entering information about customers or suppliers‚ mailing invoices to customers‚ and recording invoices received from suppliers as events in an REA diagram? The REA data model is used to develop databases that can meet both transaction
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DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm
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Chapter 3 Data Description 3-1 Measures of Central Tendency ( page 3-3) Measures found using data values from the entire population are called: parameter Measures found using data values from samples are called: statistic A parameter is a characteristic or measure obtained using data values from a specific population. A statistic is a characteristic or measure obtained using data values from a specific sample. The Measures of Central Tendency are: • The Mean • The
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about both crime and its causes and social issues. These findings are used daily by a wide cross section of society to improve every facet of our lives (Department of Criminology 2010). Today’s researchers are competent and use a variety of research methods‚ often together to change a research finding into a valuable insight that influences a decision (Department of Criminology 2010). Consequently‚ some of these research findings are sometimes critically reviewed for shortcomings strengths and future
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1 DATA TYPES Our interactions (inputs and outputs) of a program are treated in many languages as a stream of bytes. These bytes represent data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data in various way such as adding them up or sorting them. This data comes in different forms. Examples include: your name
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Tech Data Corporation Restating jumal Statements Submitted To: Prof………….. Strategy Management Stayer University Date: May 1‚ 2013 Tech Data Corporation (TECD) headquartered in Clearwater‚ FL‚ is one of the world’s largest wholesale distributors of technology products. Its supreme logistics capabilities and value added services enable 120‚000 resellers in more than 100 countries to efficiently and cost effectively support the diverse technology needs of end users. The company
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Research Project - Data Protection Data can be collected by organisations such as the websites we use daily‚ such as Facebook and Twitter. They have our information such as our age‚ date of birth‚ home address and other personal information which we would not share with strangers‚ and it is their job to protect that data‚ so that it doesn’t get into the wrong hands‚ such as scammers. Organisations may collect information from you in a number of ways‚ over the internet‚ over the phone‚ or also
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