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database models - School of Civil Engineering USM
database models - School of Civil Engineering USM

... abstract. Attributes are the characteristics of interest about entities. Values of attributes represent the actual data pertaining to specific entities in the organization or its environment. Relationships may exist between entities and are usually represented by additional attributes. For example, ...
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IOSR Journal of Computer Engineering (IOSR-JCE)

... or gain the data of the entire London city. Lastly, the architectural structure is sub divided into many entities or parts so that the data is totally secured but as per the demand of the client in order to retrieval of data it undergoes various steps which increases the access time. ...
Chapter 5 Business Intelligence: Data Warehousing, Data
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... single warehouse whereas the data reside in separate systems. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang ...
FRONTIERS OF ENTPEPRENEURSHIP RESEARCH 1988
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... With regard to intelligence (here: reasoning), there appears to be no significant correlation with business success (see Table 1). This should come as no surprise since standard psychological tests are not good predictors generally of occupational success. The attribute's typically measured are seld ...
Access Queries - College of Business
Access Queries - College of Business

... Humans can discern vague similarities and differences among data fairly easily. Computers are more exacting. Computers need you to tell them when data is a date, or a character, or a number. A zero is not the same as a blank which is not the same as a null. A null is a special character assigned to ...
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... against the dumb events. File, folder and email encryption make the clever events secure. The DESlock+ Enterprise Server ensures that security policy is enforced at all points. ...
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... from queries of laboratory information systems (LISs) for purposes including research, operations management, and QA. • Managing data searches is challenging when: – search requests originate from diverse locations in a health system – laboratories at multiple locations are supported by a single LIS ...
eDiscovery, the jargon explained.
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... the jargon explained. In the day-to-day operations of eDiscovery we use terms that may well be new to many, so to assist with our communications between new, existing and prospective client’s we have created this glossary of electronic discovery terms, set out in alphabetical order, with simple desc ...
Sorting and Queries
Sorting and Queries

... Imagine you had a database of valued customers. What if you wanted to find all the customers under thirty, living in London who spent over a £1,000 in the previous year. ...
association rule mining using sas e-miner
association rule mining using sas e-miner

... repositories. These relationships are not based on inherent properties of the data themselves (as in the case of functional dependencies), but are rather based on co-occurrence of the data items. Association rules are widely used in various areas such as telecommunication networks, market and risk m ...
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... framework based on MongoDB system to support the dynamic visualization of 3D city models. There has also been extensive research in generalization methods to populate the multiple representation databases with geographic data (see e.g. Meng and Forberg, 2007 for an overview). Mayer (2005) and Forber ...
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... Big Data can take both online and offline forms. Online Big Data refers to data that is created, ingested, trans- formed, managed and/or analysed in real-time to support operational applications and their users. Big Data is born online. Latency for these applications must be very low and availabilit ...
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IOSR Journal of Computer Science (IOSR-JCE) e-ISSN: 2278-0661, p-ISSN: 2278-8727 PP 34-38 www.iosrjournals.org
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... From many years various security-enhanced measures have been implemented to improve the security of data transmission over public networks. Existing systems for security-enhanced data transmission includes the designs of cryptographic algorithms and system infrastructures and security-enhanced routi ...
© 2011 by The 451 Group. All rights reserved
© 2011 by The 451 Group. All rights reserved

... approaches to data management – Reflects the changing data management landscape as pragmatic choices are made about data storage and analysis techniques – Processing any data applicable to analytic query • in database, data warehouse, or Hadoop, or archive ...
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... • Many data investigations are interactive data analysis “campaigns”, but HPC environments do not allow working on the login nodes • For this, we introduce the ability to reserve subclusters in Wrangler for data analysis in a cloud-like way • Allocation charged for reservation used from start of res ...
XML Data Storage
XML Data Storage

... • Map to relations – If DTD of document is known, can map data to relations – Bottom-level elements and attributes are mapped to attributes of relations – A relation is created for each element type • An id attribute to store a unique id for each element • all element attributes become relation attr ...
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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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