era of big data Manage‚ optimize and increase availability of your IBM DB2 for Linux‚ UNIX and Windows database and applications— delivering valuable intelligence to help your business users make informed decisions‚ fast Database management solutions for the era of big data 1 Introduction Accelerate development 2 Optimize performance 3 4 Increase availability 5 Give your business a competitive edge Database management solutions for the era of big data Introduction
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Data & Knowledge Engineering Introduction Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKEreaches a world-wide audience of researchers‚ designers‚ managers and users. The major aim of the journal is to identify‚ investigate and analyze the underlying principles in the design and effective use of these systems.DKE achieves this aim
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CHAPTER 2 DATA COLLECTION AND PRESENTATION 2.1 Data Collection This section aims to: 1. Identify‚ compare and contrast the different types of data; 2. List and explain the various techniques of selecting a sample; and 3. Enumerate and illustrate the different sampling techniques Types of Data Data is a collection of facts‚ such as values or measurements. It can be numbers‚ words‚ measurements‚ observations or even just descriptions of things. Two types of Data Primary Data means original
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2231-4946] Development of Data leakage Detection Using Data Allocation Strategies Rudragouda G Patil Dept of CSE‚ The Oxford College of Engg‚ Bangalore. patilrudrag@gmail.com Abstract-A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). If the data distributed to third parties is found in a public/private domain then finding the guilty party is a nontrivial task to distributor. Traditionally‚ this leakage of data is handled by water marking technique
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More than Data Warehouse- An insight to Customer Information Ritu Aggrawal – agg_ritu@rediffmail.com Deepshikha Kalra -deepshikha_ishan@yahoo.co.in working with MERI affiliated to GGSIPU‚ Delhi ABSTRACT The business requirements of an enterprise are constantly changing and the changes are coming at an exponential rate. Like advances in Information Technology have helped companies to quickly match competition. As a result‚ product quality and cost are no longer significant competitive
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12/8/2012 Major Topics Chapter 9 Using Data Flow Diagrams Data flow diagram symbols Data flow diagram levels Creating data flow diagrams Physical and logical data flow diagrams Partitioning Event driven modeling Use case and data flow diagrams Systems Analysis and Design Kendall and Kendall Fifth Edition Kendall & Kendall Using Data Flow Diagrams Unexploded data flow diagrams are useful to identify information requirements Exploded data flow diagrams can be used for presentation
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Data Mining DM Defined Is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner Process of analyzing data from different perspectives and summarizing it into useful information A class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. DM Defined The relationships and summaries derived
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CERTIFICATE OF APPROVAL This is to certify that the Seminar titled HOLOGRAPHIC DATA STORAGE Submitted by Nikhil Puthran 100942 Rahulsing Rajput 100944 Pravish Shetty 100954 Suraj Yadav 100962 In partial fulfillment of requirement for the term work of third year in Computer engineering is approved. EXTERNAL EXAMINER INTERNAL EXAMINER __________________ ___________________ HEAD OF THE DEPARTMENT INTERNAL GUIDE _____________________
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Introduction Data management within Human Resources (HR) is essential as this can be used when organisations have to make decisions‚ contact employees and also satisfy legal requirements. Aims and Objectives The aim of this report is to show the importance of why organisations must collect HR data. The objectives are: * To identify two types of data organisations must collect and how this supports HR * To describe two methods of storing HR records and the benefits of each * To explain two
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Data Gathering Techniques Data Gathering Techniques Interview • Interviews can be conducted in person or over the telephone. • Questions should be focused‚ clear‚ and encourage open-ended responses. • Interviews are mainly qualitative in nature. Data Gathering Techniques Advantages of interviews The main advantages of interviews are: • they are useful to obtain detailed information about personal feelings‚ perceptions and opinions • they allow more detailed questions to be asked • they usually
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