1. The independent data marts have inconsistent data definitions and different dimensions and measures‚ 2. Which of the following is not a major activity of OLAP? Analytics 3. Which of the following are reports that are similar to routine reports‚ Ad-hoc reports 4. Clustering techniques involves optimization this is because we want to create group that have maximum similarity among members within each group… 5. Which of the following is the reason why neural networks have been applied in business
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Lesson 3: An introduction to data modeling 3.1 Introduction: The importance of conceptual models same: understand the problem before you start constructing a solution. There are two important things to keep in mind when learning about and doing data modeling: 1. Data modeling is first and foremost a tool for communication.Their is no single “right” model. Instead‚ a valuable model highlights tricky issues‚ allows users‚ designers‚ and implementors to discuss the issues using the same vocabulary
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Storing Data In DBMS (Traditional Models) Introduction A computer database relies upon software to organize the storage of data. This software is known as a database management system (DBMS). Database management systems are categorized according to the database model that they support. The model tends to determine the query languages that are available to access the database. A great deal of the internal engineering of a DBMS‚ however‚ is independent of the data model
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Homework B – Data Centers (1) 1. PUE (Power usage effectiveness)‚ the ratio of total facility energy to IT equipment energy within a data computer‚ which measures how much of the power is actually used by the computing equipment. It is an important place to start when considering how to reduce data center power consumption because it is one of the most effective metrics for measuring data center energy efficiency. PUE is calculated by taking the total power of consumed by a data center facility
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Building Data Mining Applications for CRM Introduction This overview provides a description of some of the most common data mining algorithms in use today. We have broken the discussion into two sections‚ each with a specific theme: • Classical Techniques: Statistics‚ Neighborhoods and Clustering • Next Generation Techniques: Trees‚ Networks and Rules Each section will describe a number of data mining algorithms at a high level‚ focusing on the "big picture" so that the reader will
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Wireless carriers utilize Subscriber Data Management (SDM) systems to consolidate data in a single virtual data store with centralized administration‚ management and reporting. The “Big” part of Big Data comes from the fact that it is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. However‚ Big Data is also unstructured‚ meaning that it does not have a pre-defined data model or is not organized in a pre-defined manner
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design‚ research subjects‚ research instruments‚ preparation and construction of the questionnaires‚ reliability and validity of the research instrument‚ data gathering procedure and the statistical treatment data. Research Design A research design is the framework for a study which provides useful deadlines for collecting and analyzing data. Research design can be thought of as the logic or master plan of a research that throws light on how the study is to be conducted. It shows how all of the
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Data Ware House Normalization it’s a process of splitting data into 2 or more entities to reduce data redundancy. Normal Forms: 1. A database table must contain no repeating groups 2. All non-key attributes of a table must rely on the entire key of the table. 3. All non-key fields must depend solely on the table’s primary key. First Business Normal Form: removes repeating groups to another entity. This entity takes its name and primary (compound) key attributes‚ from the original entity and forms
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Department of Computer Science Database and Data Mining‚ COS 514 Dr. Chi Shen Homework No. 8‚ Chapter 13‚ Aklilu Shiketa Q13. 3 Cosmetic Purchases Consider the following Data on Cosmetics Purchases in Binary Matrix Form a) Select several values in the matrix and explain their meaning. Value Cell Meaning 0 For example‚ Row 1‚ Column2 At transaction #1 bag was not purchased. (shows absence of Bag in the transaction) 1 Row 10‚ column (2 and 3) “If a Bag is purchased‚ a Blush is also purchased
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and Result Interpretation 4.4.2.1 Effectiveness Criteria Results 1. Visual Promethee-based Effectiveness Analysis Visual Promethee main window is displayed that uses a typical spreadsheet to manage the data of effectiveness multi-criteria problem (Figure 4.7). The main window contain all the data have related to the PROMETHEE method (preference function‚ statistics and evaluation‚ weights…)‚ this information can be easily input and defined by the decision maker.in addition to that Visual PROMETEE
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