Chapter 5: The Data Link Layer Our goals: ❒ understand principles behind data link layer services: ❍ ❍ ❍ ❍ ❒ error detection‚ correction sharing a broadcast channel: multiple access link layer addressing reliable data transfer‚ flow control: done! instantiation and implementation of various link layer technologies 5: DataLink Layer 5-1 Link Layer ❒ ❒ ❒ ❒ ❒ 5.1 Introduction and services 5.2 Error detection and correction 5.3Multiple access protocols 5
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Data Warehousing Failures Eight studies of data warehousing failures are presented. They were written based on interviews with people who were associated with the projects. The extent of the failure varies with the organization‚ but in all cases‚ the project was at least a disappointment. Read the cases and prepare a one or two page discussion of the following: 1. What’s the scope of what can be considered a data warehousing failure? Discuss. 2. What generalizations apply across
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1. Introduction Nowadays‚ more and more people participate in the stock market. Recent survey reveals that there is a tendency of increasing number of youngsters‚ especially university students‚ get involved in the trading activities. We are no exception. Similar to many other investors‚ we are interested in forecasting the stock prices by using trends‚ patterns‚ moving averages observed from historical data. However‚ there have been a certain number of people criticizing the use of past data
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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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Financial Services Data Management: Big Data Technology in Financial Services Big Data Technology in Financial Services Introduction: Big Data in Financial Services ....................................... 1 What is Driving Big Data Technology Adoption in Financial Services?3 Customer Insight ........................................................................... 3 Regulatory Environment ................................................................ 3 Explosive Data Growth ........
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ix | 1 | INTRODUCTION | 1 | | 1.1 Background and Motivation | 1 | | 1.2 Introduction to Microarray Technology | 7 | | 1.2.1 Measuring mRNA levels | 7 | | 1.2.2 Pre-processing of Gene Expression Data | 8 | | 1.2.3 Applications of Clustering Gene Expression Data | 9 | | 1.3 Mutual Information | 10 | | 1.4 Introduction to Clustering Techniques | 11 | | 1.4.1 Clusters and Clustering | 11 | | 1.4.2 Categories of Gene Expression Data Clustering
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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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Using Data Flow Diagrams Data flow diagram is used by system analyst to put together a graphical representation of data processes throughout the organization. It depicts the broadest possible overview of system inputs‚ processes‚ and outputs. A series of layered data flow diagrams may be used to represent and analyze detailed procedures in the larger system. By using combinations of only four symbols‚ the system analyst can create a pictorial depiction of processes that will eventually provide
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A MULTIDIMENSIONAL DATA MODEL Data warehouses and OLAP tools are based on a multidimensional data model. This model views data in the form of a data cube. FROM TABLES TO DATA CUBES What is a data cube? A data cube allows data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts. In general terms‚ dimensions are the perspectives or entities with respect to which an organization wants to keep records. Each dimension may have a table associated with it‚ called
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History of Database Processing. Preliminaries Why is there a need to study File Processing and DBM? Why do we use Databases? Simply because of ourselves and there is always something that happens around us. Collect Data Use and Reuse data Historical Perspective Historical Perspective Historical Perspective Historical Perspective The Electronic Age: Diskette Punch Card Why do we Humans desire Databases? Man has always had the desire to record
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