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    Data Preprocessing

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    IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”

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    Data Protection

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    am going to explain data protection‚ talk about the data protection acts‚ rights and principles. I’m going to talk about a data controller and a data processor and what their responsibilities are. What personal and sensitive data are. What a data receiver is and what his rights are‚ what is involved in direct marketing and I will mention an example of abuse or corruption that occurred in Ireland. Data protection acts Data protection is legal control over and access to use of data stored in computers

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    big data

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    an era of big data‚ this data-driven world has the potential to improve the efficiencies of enterprises and improve the quality of our lives; however‚ there are a number of challenges that must be addressed to allow us to exploit the full potential of big data. This paper focuses on challenges faced by online retailers when making use of big data. With the provided examples of online retailers Amazon and eBay‚ this paper addressed the key challenges of big data analytics including data capture and

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    Big Data

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    having too much data‚ and what to do about them There is rarely an instance of business that you can encounter that does not involve the processing of data on information systems these days. Businesses and organizations use information systems in a majority of their functions‚ and as a result‚ are creating mass amounts of data. Because data is so crucial to business operations‚ it is being gathered‚ stored‚ and utilized in exponential amounts compared to the previous decade. These data stores can

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    Data Flow

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    DATA FLOW DIAGRAM - one of the most commonly used modeling tool which graphically represents a system as a network of processes‚ linked together through input and output flow lines and entities. Data flow Components ▪ Process - transformation of data flow into outgoing data flow. It may represent . . - whole system - subsystem - activity ▪ Data store - repository of data in the system It may represent . . . - computer file or

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    Data on Sale

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    |Case Study: Data for Sale | |Management Information System | | | |

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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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    Hero Motocorp History

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    Company History - Hero MotoCorp 1983 - Joint Collaboration Agreement with Honda Motor Co. Ltd. Japan signed 1984 - The Company was incorporated on 19th January‚ at New Delhi. The Company Manufacture motor cycles up to 100 cc capacity. The Company was promoted by Hero Cycles (P) Ltd. (HCPL). - The Company entered into a technical-cum-financial collaboration agreement with Honda Motor Co. Ltd.‚ Japan (HML). As per this collaboration agreement‚ HML was to furnish complete technical information

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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 structures

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    BCSCCS 303 R03 DATA STRUCTURES (Common for CSE‚ IT and ICT) L T P CREDITS 3 1 0 4 UNIT - I (15 Periods) Pseudo code & Recursion: Introduction – Pseudo code – ADT – ADT model‚ implementations; Recursion – Designing recursive algorithms – Examples – GCD‚ factorial‚ fibonnaci‚ Prefix to Postfix conversion‚ Tower of Hanoi; General linear lists – operations‚ implementation‚ algorithms UNIT - II (15 Periods)

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