Attributes vii. Data redundancy viii. File ix. Relation x. Meta data xi. Normalization 2. Week 7 (Hardware and Software) a. b. c. Grid computing (definitions) Cloud computing Virtualization i. PC virtualization ii. Desktop virtualization iii. Server virtualization d. Other terms i. RAM ii. CPU iii. Memory 1. Volatile memory 2. Nonvolatile memory a. 3. Week 11 Enterprise information systems focus on data warehouse Important terms and concepts i. Definitions and purposes of data warehouse ii. Definitions
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Question: 1. When developing a successful data warehouse, what are the most important risks and issues to consider and potentially avoid? Data warehouse projects have many risks. Most of them are also found in other IT projects, but data warehousing risks are more serious because data warehouses are expensive, time-and-resource demanding, large-scale projects. Each risk should be assessed at the inception of the project. When developing a successful data warehouse, it is important to carefully consider
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Fulwiler and Steve Segalewitz from IBM, discuss how understanding your online data more clearly can improve decision-making. Video demonstration of IBM/Cognos BI software applications. In the accelerating media industry, discovering relevant business insights within the chaos of available information can lead to substantial competitive advantage. IBM Business Intelligence and Analytics is designed to integrate all data providers and in-house sources to reveal timely and actionable business insights
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DATA WAREHOUSE A data warehouse is a logical collection of information gathered from different operational databases and used to create business intelligence that supports decision making tasks and business analysis activities. Walmart is known for having the biggest data warehouse used, which is larger then 4 Petabytes. Wal-Mart is very secretive about their data warehouse. After achieving a major milestone Teradata, Wal-Mart’s data warehouse supplier, was given permission to announce a few shallow
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Bhagyashree V1 The no-pain route to analytics Analytics, the trend sweeping businesses There is a new corner office and it belongs to the Chief Analytics Officer (CAO). For businesses with access to large data streams, analytics holds the key to making fast and accurate decisions. CAOs can now use data for a variety of purposes. It can help manage operational efficiencies, discover customer needs, identify new markets, give shape to new products and value-added services and develop defensible differentiators
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BUYING AND MERCHANDISING – 27/02/2014 Data warehousing: * Data warehousing is the electronic storage of all info about current customers. * Traditionally this info was used for financial and accounting purposes only. * We now use this info for marketing purposes as well. * Information is primarily gathered via the credit card base of the retailer. * Data warehouses are also used as a single source for the retailer to view key performance indicators (sales, margin, stock, profit
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analyzing, and providing access to data to help enterprise users make better business decisions. Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting and data mining. Business intelligence applications
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with Starbucks brand and image. When Starbucks first began, there wasn’t much need for business intelligence. Other than attracting customers nearby to the store, Starbucks was small enough where they did not need to worry about things like mining data. However, with the major size of Starbucks now as well as the competitive nature of the industry now, it is more crucial than ever that Starbucks utilize business intelligence resources to the best of their ability. Business intelligence is defined
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Pay Pick 'n Pay, the largest supermarket chain in South Africa, needed to sharpen its business strategy to maintain its leadership position in the retail sector. They required a highly cost-effective, scalable reporting solution that could integrate data from many operational systems into a single source of management and decision support information. They chose Sybase IQ running on Linux as part of an ongoing business intelligence operation. CUSTOMER PROFI LE SYBASE TECH NOLOGY ■ Sybase IQ
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perception of services offered. Marketing processes were greatly improved after being deemed inefficient when their data was spread over various databases and managed by outside vendors. They were previously involved with two bankruptcies but returned to profitability after going with the in-house data warehouse. They were able to use the warehouse for real-time data feeds and get real-time data results which dramatically lowered their response time to various operations throughout the companys. Delay
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