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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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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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 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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Database Management Database Management Fundamental Data Concepts REAL WORLD CHALLENGE: U.S. Xpress—Lots of Data‚ Not Enough Quality Database Structures Database Development Managing Data Resources Data Resource Management Types of Databases Data Warehouses and Data Mining Traditional File Processing The Database Management Approach F I N INFORMATION TECHNOLOGIES S S S S M S C H APTE R H I GH L I GH TS E E DATA RESOURCE MANAGEMENT L E AR NI NG OBJECT I VES
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Reform Business Technology Office The ‘big data’ revolution in healthcare Accelerating value and innovation January 2013 Peter Groves Basel Kayyali David Knott Steve Van Kuiken Contents The ‘big data’revolution in healthcare: Accelerating value and innovation 1 Introduction1 Reaching the tipping point: A new view of big data in the healthcare industry 2 Impact of big data on the healthcare system 6 Big data as a source of innovation in healthcare 10
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Data Acquisition and Interfacing Lecture 09 Introduction A data acquisition system consists of many components that are integrated to: • Sense physical variables (use of transducers) • Condition the electrical signal to make it readable by an A/D board • Convert the signal into a digital format acceptable by a computer • Process‚ analyze‚ store‚ and display the acquired data with the help of software Data Acquisition System Block Diagram Flow of information in DAQ 1. 2.
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DATABASE A database is a collection of data organized to meet users’ needs. Why This Matters Without data and the ability to process it‚ an organization would not be able to successfully engage in business activities‚ nor would it be able to generate reports to support knowledgeable workers and decision makers which in turn help’s to achieve organizational goals; it would not be able to pay employees‚ send out bills‚ and order new inventory. Databases have made it possible to map the structure
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8 3.2.0 Data collection methods 8 3.2.1 Interviews 8 3.2.2 Questionnaires 8 3.2.3 Observation 9 3.2.4 Requirement specification 9 3.2.5 Security requirements 9 3.3 System design 10 3.3.1 Logical design 10 3.3.2. Physical design 11 3.4 System implementation 11 3.4.1 Php 11 3.4.2 Mysql 11 3.4.3 Html 11 3.4.4. Dream weaver 11 3.5 System testing 11 4.0 DESIGN AND IMPLEMENTATION. 12 4.1 Introduction. 12 4.1.1 Conceptual design 12 4.1.2 Logical Design 12 4.1.2.2 Data requirement 15 4 .1.2.3 data dictionary
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to how it helps decision makers achieve the organization’s goals. 1. A(n) _________________ is a set of interrelated components that collect‚ manipulate‚ and disseminate data and information and provide a feedback mechanism to meet an objective. 2. What consists of raw facts‚ such as an employee number? a. bytes b. data c. information d. knowledge Knowing the potential impact of information systems and having the ability to put this knowledge to work can result in a successful personal
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