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    Enterprise Data Model

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    The Enterprise Data Model Introduction An Enterprise Data Model is an integrated view of the data produced and consumed across an entire organization. It incorporates an appropriate industry perspective. An Enterprise Data Model (EDM) represents a single integrated definition of data‚ unbiased of any system or application. It is independent of "how" the data is physically sourced‚ stored‚ processed or accessed. The model unites‚ formalizes and represents the things important to an organization

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    DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm

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    Data Flow Diagram

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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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    Data Comm

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    must-have software in every PC or Laptops. Nowadays‚ there are more than a dozen alternative web browser we can use but the famous web browser that we all know are Google Chrome‚ Mozilla Firefox‚ Safari‚ Rockmelt and Internet Explorer. This are the example photos of the famous web browser :- Figure 1: Google Chrome Figure 2: Safari Figure 3: Mozilla Firefox Figure 4: Internet Explorer Figure 5: Rockmelt 2.0 Problem Statement Althought there are many kind of web browser

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    Qualitative Data

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    READING QUESTIONS DAY ANSWERS 1. Which of the following reading components do you find the easiest and the most difficult? Vocabulary Sentence/Syntax Getting the main idea Comprehension Others:_______________ Easiest: _____________ Difficult: _______________ EASIEST COMPONENTS: Vocabulary - 3 Sentence/Syntax - 11 Getting the main idea - 16 Comprehension - 1 DIFFICULT COMPONENTS: Vocabulary - 5 Sentence/Syntax - 9 Getting the main idea - 5 Comprehension – 11 2. Why do you

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    Data Interpretion

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    MEAN SCORE Descriptive Statistics N Mean Std.Deviation Discount 196 1.38 .672 Gift Coupon 196 1.47 .603 Free tour 196 1.91 .929 Cash back 196 1.44 .634 Price 196 1.54 .753 Quality 196 1.44 .592 Quantity 196 1.58 .715 Varity 196 1.68 .609 Brand 196 1.66 .641 Durability 196 1.94 .732 Availability 196 2.04 .902 Promotion Scheme 196 2.24 .944 Advertisement 196 2.10 .871 Promotional scheme of Berger paint is very attractive. 196 1.99 .791

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    Data Mining Soltions

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    contains only three base cells: (1) (a1‚ b2‚ c3‚ d4; ...‚ d9‚ d10)‚ (2) (a1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ and (3) (b1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ where a_i != b_i‚ b_i != c_i‚ etc. The measure of the cube is count. 1‚ How many nonempty cuboids will a full data cube contain? Answer: 210 = 1024 2‚ How many nonempty aggregate (i.e.‚ non-base) cells will a full cube contain? Answer: There will be 3 ∗ 210 − 6 ∗ 27 − 3 = 2301 nonempty aggregate cells in the full cube. The number of cells overlapping twice is 27

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    Environment Data

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    Environmental Studies For Undergraduate Courses subhamsahu CORE MODULE SYLLABUS FOR ENVIRONMENTAL STUDIES FOR UNDER GRADUATE COURSES OF ALL BRANCHES OF HIGHER EDUCATION Vision The importance of environmental science and environmental studies cannot be disputed. The need for sustainable development is a key to the future of mankind. Continuing problems of pollution‚ loss of forget‚ solid waste disposal‚ degradation of environment‚ issues like economic productivity and national security

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    5.3.3 Data cleaning Data cleaning helps to remove all unnecessary data. Data cleaning attempts to fill in missing values‚ smooth out noise while identifying outliers and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation. 5.3.4 Data analysis Data analysis is also known as analysis of data or data analytics‚ is a process of inspecting‚ cleansing‚ transforming and modeling data with the goal of discovering

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    Data Mining Information

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    1 Define data mining. Why are there many different names and definitions for data mining? Data mining is the process through which previously unknown patterns in data were discovered. Another definition would be “a process that uses statistical‚ mathematical‚ artificial intelligence‚ and machine learning techniques to extract and identify useful information and subsequent knowledge from large databases.” This includes most types of automated data analysis. A third definition: Data mining is the

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