"Exploratory data analysis" Essays and Research Papers

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    The New Frontier: Data Analytics Yvonne Mitchell Strayer University Professor Raied Salman Info Syst Decision-Making January 12‚ 2015 The New Frontier: Data Analytics What is data analytics? How has its use in business evolved over time? What are the advantages and disadvantages of using data analytics within a specific company or industry? Are there any challenges or obstacles that business management must overcome in order to implement data analytics? If so‚ is there a strategy that

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    CHAPTER – I INTRODUCTION 1.1 OUTLINE OF THE PROJECT: A job analysis is a step-by-step specification of an employment position ’s requirements‚ functions‚ and procedures. Just as a seed cannot blossom into a flower unless the ground is properly prepared‚ many human resource management (HRM) practices cannot blossom into competitive advantage unless grounded on an adequate job analysis.  Successful HRM practices can lead to outcomes that create competitive advantage. Job analyses

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    Big Data Architecture‚ Goals and Challenges Cipson Jose Chiriyankandath Dakota State University Abstract Big Data inspired data analysis is matured from proof of concept projects to an influential tool for decision makers to make informed decisions. More and more organizations are utilizing their internally and externally available data with more complex analysis techniques to derive meaningful insights. This paper addresses some of the architectural goals and challenges for Big Data architecture

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    3.6 Data Collection Procedure Figure 3.1 Data Collection Procedure The methods that was used for this study are open-ended survey and semi-structured interview. Since the method is only these two methods‚ the data collection procedure is almost the same for both the methods. The first step for both the procedure is to get the letter of acknowledgement from the faculty that the researcher is doing the research upon the selected respondents for Final Year Project purpose and that there is prove

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    Global Data Analytics Outsourcing Market 2014-2018 Organizations have a tremendous amount of data in departments such as HR‚ procurement‚ production‚ or sales and marketing. Data analysis is required to use these data efficiently. The data analytics allows enterprises to gain insights in several fields‚ for instance‚ consumer insights‚ which is how customers behave‚ and other market-related insights. Data analytics outsourcing is the process in which organizations employ service providers to perform

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    Benefits of Fleet Management Data Integration NAME DBM 502 University of Phoenix Benefits of Fleet Management Data Integration Abstract Huffman Trucking maintains extensive vehicle fleet maintenance logs‚ with data on vehicles‚ parts‚ tires‚ maintenance‚ warranty‚ costs and dates of service. Management wants to know whether it would be strategically advisable to integrate this information into their current data warehouse and how to leverage it. Investigation shows that there could be significant

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    design‚ research subjects‚ research instruments‚ preparation and construction of the questionnaires‚ reliability and validity of the research instrument‚ data gathering procedure and the statistical treatment data. Research Design A research design is the framework for a study which provides useful deadlines for collecting and analyzing data. Research design can be thought of as the logic or master plan of a research that throws light on how the study is to be conducted. It shows how all of the

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    Secondary research data in a digital age Advantages of secondary data. 1. Availability. Is faster and less expensive when researchers use electronic retrieval to access data stored digitally. 2. Money and time are some things that researchers need to save up and when they can access to the information in such a short amount of time and for free‚ they can be using that extra time and money in some other things 3. Secondary data are essential in instances when data simply cannot be obtained

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    SPECIAL REPORT Big Data AnalyticsDeep Dive Deriving Meaning From the Data Explosion © Copyright InfoWorld Media Group. All rights reserved. Sponsored by i Big Data AnalyticsDeep Dive Making sense of big data New analysis tools and abundant processing power unlock critical insights from unfathomable volumes of corporate and external data i By David S. Linthicum THE ABILITY TO DERIVE MEANING quickly from huge quantities of structured and unstructured data has been an objective

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    Overview: Chapter 2 Data Mining for Business Intelligence Shmueli‚ Patel & Bruce Core Ideas in Data Mining Classification Prediction Association Rules Data Reduction Data Visualization and exploration Two types of methods: Supervised and Unsupervised learning Supervised Learning Goal: Predict a single “target” or “outcome” variable Training data from which the algorithm “learns” – value of the outcome of interest is known Apply to test data where value is not known and will be predicted

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