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    Organisational Structure

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    Organisation Structure Every organisation has a specific structure run the business as per the requirement. The main function is business function and rest are support functions. Depending on the functions department forms. The sub departments or sub functions called verticals. The pyramid structure of organisational rule applies in all departments. Department or function is headed by department heads and verticals are headed by vertical heads who reports to department heads. In organisation

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    Organizational Structure

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    OrganizationalOrganizational structure is needed in organizations to arrange employees and their jobs in a certain category to help meet business goals and needs. Procedures are established that assign responsibilities for various functions. These decisions help determine organizational structure (Madapusi‚ 2008). Organizational structure allows greater effectiveness in organizations. Different types of organizations such as Baker Hughes Drilling Fluids‚ Atlanta Memorial Hospital‚ Doyenne Constructors

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    Big Data

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    A glimpse of Big Data Jan. 2013 What is big data? “Big data is not a precise term; rather it’s a characterization of the never ending accumulation of all kinds of data‚ most of it unstructured. It describes data sets that are growing exponentially and that are too large‚ too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes‚ the precise amount is less the issue than where the data ends up and how it is used.”------Cite from EMC’s report

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    Data Mining

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    Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9‚ 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model‚ which has‚ in turn been trained over your data‚ learning from the experience

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    Data Mining

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    Nagham Hamid‚ Abid Yahya‚ R. Badlishah Ahmad & Osamah M. Al-Qershi Image Steganography Techniques: An Overview Nagham Hamid University Malaysia Perils (UniMAP) School of Communication and Computer Engineering Penang‚ Malaysia nagham_fawa@yahoo.com Abid Yahya University Malaysia Perlis (UniMAP) School of Communication and Computer Engineering Perlis‚ Malaysia R. Badlishah Ahmad University Malaysia Perlis (UniMAP) School of Communication and Computer Engineering Perlis‚ Malaysia

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    Hatco Data

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    HATCO Data Set Description The HATCO data set gives data from a survey of customers of the HATCO company. The data set consists of 100 observations on 14 separate variables. Three types of information were collected. The first type of information is the perception of HATCO on seven attributes identified in past studies as the most influential in the choice of suppliers. The respondents‚ purchasing managers of firms buying from HATCO‚ rated HATCO on each attribute. Each of these 7 variables

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    Data Security

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    Master Thesis Electrical Engineering November 2011 Security Techniques for Protecting Data in Cloud Computing Venkata Sravan Kumar Maddineni Shivashanker Ragi School of Computing Blekinge Institute of Technology SE - 371 79 Karlskrona Sweden i This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to 40 weeks of full time studies.

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    theories of relationship breakdown . Stephanie Rollie and Steve Duck developed a model of the termination of close and intimate relationships in 2006.This model focuses on the processes that typify relationship breakdown ‚ rather than being tied to distinct phases that people pass through . The 6 stages may appear to overlap or have common features but also serve very different purposes and ultimately have different consequences. Initially ‚ the first stage is breakdown ‚ this is where one of

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    Big DATA

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    4V of Big Data? Imagine all the information you alone generate each time you swipe your credit card‚ post to social media‚ drive your car‚ leave a voicemail‚ or visit a doctor. Now try to imagine your data combined with the data of all humans‚ corporations‚ and organizations in the world! From healthcare to social media‚ from business to the auto industry‚ humans are now creating more data than ever before. volume‚ velocity‚ variety‚ and veracity. Volume: Scale of Data Big data is big. It’s

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    Data Quality

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    PRINCIPLES OF DATA QUALITY Arthur D. Chapman1 Although most data gathering disciples treat error as an embarrassing issue to be expunged‚ the error inherent in [spatial] data deserves closer attention and public understanding …because error provides a critical component in judging fitness for use. (Chrisman 1991). Australian Biodiversity Information Services PO Box 7491‚ Toowoomba South‚ Qld‚ Australia email: papers.digit@gbif.org 1 © 2005‚ Global Biodiversity Information Facility Material

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