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Online data collection CHew
Online data collection CHew

... Unobtrusive Approaches Observation using traces and archives, e.g. discussion group archives, browsing behaviours, social networking links (SNA); lurking? ...
The Junior Digital Producers
The Junior Digital Producers

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OLAP, OLTP for DECISION-MAKING PROCESS using Data Mining

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Emerging Research Directions in DBs/ISs
Emerging Research Directions in DBs/ISs

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Major – Data Analytics (120 credits)
Major – Data Analytics (120 credits)

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Literature Review of Issues in Data Warehousing and OLTP, OLAP
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Overcoming the Technical and Policy Constraints That Limit Large
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Module 5 Data Warehousing - University of Colorado Boulder
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... ii. A minimum sample size of 30 is needed or both populations need to be normally distributed. Note if the sample size is less than 30, we simply assume a normal distribution. b. Suppose we don’t know what σ2 is but we have good reason to believe it should be the same across samples. i. A common exa ...
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... such as subsalt and sub-basalt structures, as well as being problematic for processes such as pre-stack inversion, where low frequencies are critical to achieving a stable inversion result. A number of solutions to the problem of the ghost effect have been proposed, which can be conveniently (though ...
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Database System Concepts and Architecture - Home

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Business intelligence

Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.BI can be used to support a wide range of business decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a more complete picture which, in effect, creates an ""intelligence"" that cannot be derived by any singular set of data.
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