Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse
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business intelligence‚ data warehouse‚ data mining‚ text and web mining‚ and knowledge management. Justify and synthesis your answers/viewpoints with examples (e.g. eBay case) and findings from literature/articles. To understand the relationships between these terms‚ definition of each term should be illustrated. Firstly‚ business intelligence (BI) in most resource has been defined as a broad term that combines many tools and technologies‚ used to extract useful meaning of enterprise data in order to help
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DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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Introduction Data communications (Datacom) is the engineering discipline concerned with communication between the computers. It is defined as a subset of telecommunication involving the transmission of data to and from computers and components of computer systems. More specifically data communication is transmitted via mediums such as wires‚ coaxial cables‚ fiber optics‚ or radiated electromagnetic waves such as broadcast radio‚ infrared light‚ microwaves‚ and satellites. Data Communications =
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The Big Data Challenges Lamin A Tunkara CIS 500 – Information Systems for Decision Making Dr. Edwin OTTO July 16‚ 2013 Abstract The paper explores the challenges of big data and the strategies deployed by Volvo Car Corporation in instituting an information technology infrastructural tool that helped the company tap into its massive data‚ bank to extract information for meaningful process improvements. The paper culled information from Dumbill (2012) who in an article
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The Acquisition Process Competition Requirements Choconda Martin BUS 319 November 5‚ 2012 Professor Calvin D. Fogle Almost all DOD systems are competed at some stage in the acquisition system (we would guess that less than 10% of acquisition programs do not go through a competitive process at least once in their acquisition cycle). Generally‚ the sequence is: • Define the requirement (determine the mismatch between operational capability--more
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CHAPTER 12 ROUTING IN SWITCHED NETWORKS A NSWERS TO Q UESTIONS 12.1 The average load expected over the course of the busiest hour of use during the course of a day. 12.2 The tradeoff is between efficiency and resilience. 12.3 A static routing strategy does not adapt to changing conditions on the network but uses a fixed strategy developed ahead of time. With alternate routing‚ there are a number of alternate routes between source and destination and a dynamic choice of routes is
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Data Analysis‚ Presentation & Interpretation Prof. Dr. Md. Nazrul Islam Ph.D 1 Data Analysis Plan The appropriate methods of data analysis are determined by your data types and variables of interest‚ the actual distribution of the variables‚ and the number of cases. 2 Data Management 3 Why prepare a plan for processing and analysis of data? All information has been collected in a standardized way Not collected unnecessary data which will never be analyzed A statistical analysis plan should
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Impact of Mergers and Acquisitions on Employee Motivation- Telecommunication Merger in the UK A case of T-Mobile and Orange Mobile Merger Abstract Over the past one decade‚ mergers and acquisitions increased at a record rate globally‚ especially in the United States. The telecommunication sector experienced no exclusion to this phenomenon and the three major telecommunication mergers included MCI and Verizon‚ Sprint and Nextel‚ and BellSouth and AT&T. As a result‚ the telecom playfield
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Troy Wilson* suggest a way for preserving and enhancing the value of exploration data E very year explorationists‚ industrywide‚ collect billions of dollars worth of data. Yet‚ when it comes time for geologists to extract value from their information‚ they often find that value has been lost through poor practices in data management. There is no reliable record of the data that has been collected or data is not where it should be - it has been misplaced or corrupted. Re-assembling information
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