Research design and Methods ……………………………………………...…………………05 Population and Sample Study ……………………………………...……………………05 Sample Size ……………………………………………………...………………………05 Source of Data ………………………………………………...…………………………05 Collection of Data ……………………...………………………………………………..06 Data Management …………………………………………...…………………………..06 Data Analysis Strategy ……………………………..…………………………………...07 Strengths and Weaknesses …………………………………………………………………….08 Strengths ……………………………………………………………...…………………08 Weaknesses ……………………………………………………………………………
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without data, information and knowledge. Data, information and knowledge are different from one another, yet there are interrelated to each other. Data Data are unprocessed raw facts which can be either qualified and or quantified. It explains phenomenal refer to statistical observations and other recordings or collections of evidence (Chaim Zins, 2007, p.480). Data can be in numbers or text. For example, temperature currency, gender, age, body weight. Figure 1, is example of data recorded
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interaction? The Internet of Things(IoT) helps create an environment in which machines can interact amongst themselves or with living beings (human, animals and plants), where each entity is provided with unique identifiers and the ability to transfer data over a network without any human-to-human or human-to-machine interaction (Wigmore, 2014). IoT is a generic term and all entities play an active role owing to their connection to the Internet. It provides access to information, media and services
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or traditional data processing applications. The challenges include capture, curation, storage,[3] search, sharing, transfer, analysis,[4] and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime
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Database Partitioning JOHN OWENS West Florida University Data Management March 18, 2014 Data partitioning is a tool that can help manage the day-to-day needs of an organization. Each organization has unique values that drive business. All organizations have policies and processes that are influenced by their environment and industry. The use of data partitioning can help productivity by recognizing the need to categorize data to tailor unique needs. This approach does require some effort
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addition, generation of highly customized circuits does not integrate nicely with high level synthesis tools. In this work, we introduce TARCAD, a template architecture to design reconfigurable accelerators. TARCAD enables high customization in the data management and compute engines while retaining a programming model based on generic programming principles. The template features generality and scalable performance over a range of FPGAs. We describe the template architecture in detail and show how
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order to achieve the objectives of increasing the production and decreasing the cost. This study is using systematic observation, interview with discussion and stopwatch time study. Statistically Fit and Production Modeler software is used to test the data and make improvements. By stating the time standard for the process involving manpower, production rate increase and the cost will be less. Other than that, proposal for improvement could be made in order to enhance the effort to achieve the main objective
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of an information system are people, hardware resources, software resources, data resources, and network resources. (2010). People include the end-users and also the programmers, analysts, and other technical specialists that support the system. Hardware resources include the servers, client workstations, monitors, keyboards, and all other peripherals that interconnect them. Human interface devices allow users to input data to the system, which is translated into usable information. Software resources
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Big Data is a type of new era that will help the competition of companies to capture and analyze huge volumes of data. Big data can come in many forms. For example, the data can be transactions for online stores. Online buying has been a big hit over the last few years, and people have begun to find it easier to buy their resources. When the tractions go through, the company is collecting logs of data to help the company increase their marketing production line. These logs help predict buying patterns
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| | | Identify the Problems Analysis of gathered data Medialogic Pakistan Ltd. is currently not analyzing the gathered data. Although at the current stage gathering first hand information is very useful for companies, but a lot further analysis can give more valuable insight for the channel operators. User profiles may be inaccurate
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