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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    Data Migration

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    Data migration • Data migration is the process of transferring data between storage types‚ formats‚ or computer systems. • Data migration is usually performed programmatically to achieve an automated migration‚ freeing up human resources from tedious tasks. • It is required when organizations or individuals change computer systems or upgrade to new systems. • To achieve an effective data migration procedure‚ data on the old system is mapped to the new system providing a design

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    Statistics and Data

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    Residuals Date: _____________________ Introduction The fit of a linear function to a set of data can be assessed by analyzing__________________. A residual is the vertical distance between an observed data value and an estimated data value on a line of best fit. Representing residuals on a___________________________ provides a visual representation of the residuals for a set of data. A residual plot contains the points: (x‚ residual for x). A random residual plot‚ with both

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    Data Mining

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    SMS CUSAT Reading Material on Data Mining Anas AP & Alex Titty John • What is Data? Data is a collection of facts and information or unprocessed information. Example: Student names‚ Addresses‚ Phone Numbers etc. • What is a Database? A structured set of data held in a computer which is accessible in various ways. Example: Electronic Address Book‚ Phone Book. • What is a Data Warehouse? The electronic storage of large amount of data by business. Concept originated in

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    Empirical data

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    research because they allow the researchers to analyze empirical data needed to interpret the findings and draw conclusions based on the results of the research. According to Portney and Watkins (2009)‚ all studies require a description of subjects and responses that are obtained through measuring central tendency‚ so all studies use descriptive statistics to present an appropriate use of statistical tests and the validity of data interpretation. Although descriptive statistics do not allow general

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    Data Preprocessing

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    Data Preprocessing 3 Today’s real-world databases are highly susceptible to noisy‚ missing‚ and inconsistent data due to their typically huge size (often several gigabytes or more) and their likely origin from multiple‚ heterogenous sources. Low-quality data will lead to low-quality mining results. “How can the data be preprocessed in order to help improve the quality of the data and‚ consequently‚ of the mining results? How can the data be preprocessed so as to improve the efficiency and ease

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    Data Warehousing

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    and Kimball’s definition of Data Warehousing. Bill Inmon advocates a top-down development approach that adapts traditional relational database tools to the development needs of an enterprise wide data warehouse. From this enterprise wide data store‚ individual departmental databases are developed to serve most decision support needs. Ralph Kimball‚ on the other hand‚ suggests a bottom-up approach that uses dimensional modeling‚ a data modeling approach unique to data warehousing. Rather than building

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    Data Research

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    Data Collection: Data collection is the heart of any research. No study is complete without the data collection. This research also includes data collection and was done differently for different type of data. TYPES OF DATA Primary Data: For the purpose of collecting maximum primary data‚ a structured questionnaire was used wherein questions pertaining to the satisfaction level of the customer about pantaloons product(apparel)‚ the quality‚ color‚ variety of products‚ the availability of different

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    Data Managament

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    you an understanding of how data resources are managed in information systems by analyzing the managerial implications of basic concept and applications of database management. Introduce the concept of data resource management and stresses the advantages of the database management approach. It also stresses the role of database management system software and the database administration function. Finally‚ it outlines several major managerial considerations of data resource management.

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    Data Encryption

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    its simplest terms‚ the translation of data into a secret code. In order to read an encrypted file‚ the receiver of the file must obtain a secret key that will enable him to decrypt the file. A deeper look into cryptography‚ cryptanalysis‚ and the Data Encryption Standard (DES) will provide a better understanding of data encryption. Cryptographic Methods There are two standard methods of cryptography‚ asymmetric encryption and symmetric encryption. Data that is in its original form (unscrambled)

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