John Smith Dr. Daniels 2/14/13 Chapter 5 Video Case 1. Data warehouses store current as well as historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons. REI is building a data warehouse because they want to better serve their customers with their products. The data ware house allows REI to make the customers experience with their company a much more fulfilling one ensuring their return. 2. Consumer cooperatives
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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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Data Warehouses and Data Marts: A Dynamic View file:///E|/FrontPage Webs/Content/EISWEB/DWDMDV.html Data Warehouses and Data Marts: A Dynamic View By Joseph M. Firestone‚ Ph.D. White Paper No. Three March 27‚ 1997 Patterns of Data Mart Development In the beginning‚ there were only the islands of information: the operational data stores and legacy systems that needed enterprise-wide integration; and the data warehouse: the solution to the problem of integration of diverse and often redundant
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The impacts of implementing a data warehouse in the banking industry Data warehousing in the financial sector Introduction In the modern banking and financial sector‚ there is keener and stronger competition and many enterprises are much more eager to get immediate and accurate information to make better and faster decisions. Furthermore‚ with many banks fighting to capture new customers and the rapidly growing need for larger amounts and more specific information‚ traditional databases are incapable
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current data to visualize the trend of future. While data is considered authenticated‚ correct data is required for the management to take any further steps. Hence‚ technical personnel will be very concerned about data extraction. Every possibility of erroneous data must be captured. So‚ what we get is that data need to be transformed into valuable information which is possible only when BI team is highly optimized with their tasks. Understanding each and every single details related to data is
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More than Data Warehouse- An insight to Customer Information Ritu Aggrawal – agg_ritu@rediffmail.com Deepshikha Kalra -deepshikha_ishan@yahoo.co.in working with MERI affiliated to GGSIPU‚ Delhi ABSTRACT The business requirements of an enterprise are constantly changing and the changes are coming at an exponential rate. Like advances in Information Technology have helped companies to quickly match competition. As a result‚ product quality and cost are no longer significant competitive
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Fig: Architecture of data warehouse Operations Conceiving data as a cube with hierarchical dimensions leads to conceptually straightforward operations to facilitate analysis. Aligning the data content with a familiar visualization enhances analyst learning and productivity.[5] The user-initiated process of navigating by calling for page displays interactively‚ through the specification of slices via rotations and drill down/up is sometimes called "slice and dice". Common operations
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be comparing and contrasting transactional databases and data warehouses‚ demonstrating the similarities and differences between them both. I will do this by first defining these database systems and the reason for their use. I will also be using key relevant theories and tools to back up my findings‚ to argue their differences and similarities as efficiently as possible. Where similarities between transactional databases and data warehouses do exist they are in the areas of information storage and
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Chapter: Chapter01: Organizational Performance: IT Support and Applications Multiple Choice 1. To survive and succeed in the New Economy‚ Orbis Inc.’s supply chain model was transformed from a: a) hub-like supply chain to a linear supply chain. b) linear supply chain to a hub-like supply chain. c) multiple layer supply chain to a single layer supply chain. d) single layer supply chain to a multiple layer supply chain. e) spoke like Ans: b Section Ref 1-1 Difficulty: Moderate
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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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