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    Data Warehousing

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    Data Warehousing‚ Data Marts and Data Mining Data Marts A data mart is a subset of an organizational data store‚ usually oriented to a specific purpose or major data subject‚ that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse‚ though in the bottom-up data warehouse design methodology the data

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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    Data Description

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    Chapter 3 Data Description 3-1 Measures of Central Tendency ( page 3-3) Measures found using data values from the entire population are called: parameter Measures found using data values from samples are called: statistic A parameter is a characteristic or measure obtained using data values from a specific population. A statistic is a characteristic or measure obtained using data values from a specific sample. The Measures of Central Tendency are: • The Mean • The

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    Big Data

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    Table of Contents 1. VARIABLES- QUALITATIVE AND QUANTITATIVE......................3 1.1 Qualitative Data (Categorical Variables or Attributes) ........................... 3 1.2 Quantitative Data............................................................................................... 4 DESCRIPTIVE STATISTICS.................................................6 2.1 Sample Data versus Population Data ................................................................... 6 2.2 Parameters and Statistics

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    Data Recovery

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    Data Recovery Book V1.0 (Visit http://www.easeus.com for more information) DATA RECOVERY BOOK V1.0 FOREWORD ---------------------------------------------------------------------------------------------------------------------The core of information age is the information technology‚ while the core of the information technology consists in the information process and storage. Along with the rapid development of the information and the popularization of the personal computer‚ people find information

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    Data Mining

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    were selected (static and dynamic complexity index) and a Business Dynamic model was developed. This model was used with empirical data collected in a job shop manufacturing system in order to test the usefulness and validity of the dynamic complex index. The Business Dynamic model analyzed the trend of the index in function of different inputs in a selected work center. The results showed that the maximum value of the dynamic complexity index represents the so called “edge of chaos”‚ where the amount

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    Data Structure

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    WXES1115/WXES1117 Data Structures Lab 10: Queue 1. Write a generic queue class called MyQueue using LinkedList. Implement the following methods: a. public void enqueue(E o) b. public E dequeue() c. public E peek() d. public int getSize() e. public boolean isEmpty(); f. public String toString() public static void main(String[] args) { // TODO code application logic here MyQueue <String > fruitQ = new MyQueue <String >();

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    Big Data

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    Case Study Italian retailer Unicomm selects Huawei RH5885 V2 server for its SAP HANA database and S7700 and S5700 switches. Huawei’s SAP HANA application came about as a result of a successful switching project and helps Unicomm to analyse sales data in real time. “With the SAP HANA solution‚ we needed a partner that was ready to support us in every way possible. By helping us to stay in budget and to adopt a system that could grow in line with company requirements‚ Huawei really delivered.” Federico

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    Quality Center Tool

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    Lifecycle Management (ALM) 11.00 HP Quality Center 11.00 Roman Zednik HP Software Austria WARUM 11? QC Product Release Overview Product Name Version Previous Version Previous Name Release HP Test Data Management HP ALM 1.0 11.0 N/A 10.0 (derived from HP DB Archiving 6.2) HP QC Premier HP Q3 17-092010 HP Quality Center Enterprise HP Quality Center Starter HP Functional Test HP Service Test HP Performance Center 11.0 11.0 11.0 11.0 11.0 10.0 10.0

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    Data Comms

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    starts here" and "Internet of Everything" advertising campaigns. These efforts were designed to position Cisco for the next ten years into a global leader in connecting the previously unconnected and facilitate the IP address connectivity of people‚ data‚ processes and things through cloud computing applications and services. Cisco’s current portfolio of products and services is focused upon three market segments—Enterprise and

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