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    Data Models

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    Data Models Consider a simple student registration. Specifically we want to support the tasks of students registering for or withdrawing from a class. To do this‚ the system will need to record data about what entities? What specific data about the entities will need to be stored? What is the cardinality between students and courses? Diagram the data model. While‚ considering a student class registration system for registering or withdrawing a system must have the capability to record data in

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    Data Types

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    LECTURE 1 DATA TYPES Our interactions (inputs and outputs) of a program are treated in many languages as a stream of bytes. These bytes represent data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data in various way such as adding them up or sorting them. This data comes in different forms. Examples include: your

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    Data Collection

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    Data collection is any process of preparing and collecting data‚ for example‚ as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record‚ to make decisions about important issues‚ or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project‚ and is often formalized through a data collection plan which often

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    Big Data

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    Big Data which companies are easily able to collect from their businesses‚ customers and employees. It explains the numerous advantages of using the data collected by companies effectively so that it can be used by the company in improving its efficiencies‚ sales‚ faster and quicker turnaround which in turn would lead to increase revenues and finally increased profits (which is what the stakeholders of the company are looking for).It illustrates the prominent fact that companies that are data-driven

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    Customer Data

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    Enhancing Customer Data Enhanced Customer Data Repository is a secure and fully supported data repository with problem determination tools and functions. It updates problem management records (PMR) and maintains full data life cycle management. · combination of all the internal structured business data (CRM‚ ERP‚ POS and all the internal system data) and external unstructured data ( Social media data‚ feedback surveys‚ Audios‚ Videos‚ streaming data‚ Call center data‚ images) · unmanageable volumes

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    Data Warehouse

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    Data Warehouse Concepts and Design Contents Data Warehouse Concepts and Design 1 Abstract 2 Abbreviations 2 Keywords 3 Introduction 3 Jarir Bookstore – Applying the Kimball Method 3 Summary from the available literature and Follow a Proven Methodology: Lifecycle Steps and Tracks 4 Issues and Process involved in Implementation of DW/BI system 5 Data Model Design 6 Star Schema Model 7 Fact Table 10 Dimension Table: 11 Design Feature: 12 Identifying the fields from facts/dimensions: MS: 12 Advanced

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    data abstruction

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    WEEK-3 Data Abstraction Destructors • Destructors are functions without any type • The name of a destructor is the character ’~’ followed by class name – For example: ~clockType(); • A class can have only one destructor – The destructor has no parameters • Destructor automatically executes when the class object goes out of scope C++ Programming: Program Design Including Data Structures‚ Sixth Edition 2 Data Abstract‚ Classes‚ and Abstract Data Types • Abstraction – i

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    Data Mining

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    Data mining Data mining is simply filtering through large amounts of raw data for useful information that gives businesses a competitive edge. This information is made up of meaningful patterns and trends that are already in the data but were previously unseen. The most popular tool used when mining is artificial intelligence (AI). AI technologies try to work the way the human brain works‚ by making intelligent guesses‚ learning by example‚ and using deductive reasoning. Some of the more popular

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    Comparative Data

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    Associate Level Material Comparative Data Resource: Ch. 14 of Health Care Finance Complete the following table by writing responses to the questions. Cite the sources in the text and list them at the bottom of the table. What criterion must be met for true comparability? | For true comparability‚ consistency‚ verification and unit measurement must be met. Consistency is vital to make sure that all things are done in the same manner throughout the same time period. Verification is

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    Data Integrity

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    Types of Data Integrity This section describes the rules that can be applied to table columns to enforce different types of data integrity. Null Rule A null rule is a rule defined on a single column that allows or disallows inserts or updates of rows containing a null (the absence of a value) in that column. Unique Column Values A unique value rule defined on a column (or set of columns) allows the insert or update of a row only if it contains a unique value in that column (or set of columns)

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