insight into the usage of data warehousing and data mining techniques to enhance the productivity of the business. The study of the processes is analysed so as to get the need of adaptation according to inherent demands of these industries in near future. The main topics we are discussing here are: a) Data warehousing b) Data Mining c) ETL d) Data Mart An attempt has been made to analyse different ways of using these for the enhancement in the different field. Data warehousing and current
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Data warehousing is the process of collecting data in raw form for analyzing trends. The benefits to data warehousing are improved end-user access‚ increased data consistency‚ various kinds of reports can be made from the data collected‚ gather the data in a common place from separate sources and additional documentation of data. Potential lower computing costs‚ increased productivity‚ end-users can query the database without using overhead of the operational systems and creates an infrastructure
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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 Warehousing‚ Data Marts and Data Mining Data Marts A data mart is a subset of an organizational data store‚ usually oriented to a specific purpose or major data subject‚ that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse‚ though in the bottom-up data warehouse design methodology the data
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Data Warehousing and Data mining December‚ 9 2013 Data Mining and Data Warehousing Companies and organizations all over the world are blasting on the scene with data mining and data warehousing trying to keep an extreme competitive leg up on the competition. Always trying to improve the competiveness and the improvement of the business process is a key factor in expanding and strategically maintaining a higher standard for the most cost effective means in any
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Corporation WaveGuide is an early stage mobile analytical instrument company building a suite of next generation handheld (i) infrared and (ii) nuclear magnetic resonance spectrometers for portable use in multiple untapped markets. WaveGuide’s business model: •Acquire exclusive worldwide licensing for existing handheld infrared spectrometer technologies for placement into large unrealized markets (to be licensed from defense company already earning $MM revenues from its existing products); •Acquire exclusive
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Service Request Memo Normalization Cynthia Erney Database Concepts DBM/381 August 21‚ 2012 Nongxin Rao‚ PhD To: the Technical Services/Logistics Manager at Taylor Ambulance RE: Service Request SR-ta-001 Scheduling System Database This memo is to inform you that your service request SR-ta-001 has reached my desk and currently is in the process of being completed. The purpose of this memo is to report the progress on the service requests. Currently I am in the stage of normalizing the database
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Information Systems Management Research Project ON Data Warehousing and Data Mining Submitted in Partial fulfilment of requirement of award of MBA degree of GGSIPU‚ New Delhi Submitted By: Swati Singhal (12015603911) Saba Afghan (11415603911) 2011-2013
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1 Normalization Procedure for Class XII Board Marks In view of large scale variations in the examination system in country‚ the JEE Interface Group (JIG) decided that for this year (2013)‚ 50% of Boards marks be normalized by equating percentile amongst different boards/examining bodies and anchoring them to All India JEE-Main percentiles‚ and 50% be normalized by equating each Board’s/examining Body’s percentile with JEE(Main) percentile marks of respective Boards /examining bodies. Accordingly
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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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