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Non-interoperable Systems Phase Out
Non-interoperable Systems Phase Out

... come with search-engine companies’ entry into the geospatial information market. "MapInfo revenue has doubled since AOL bought MapQuest," said George Moon of MapInfo. "Google, Yahoo and Microsoft want mind- ...
Data Management in Geodise
Data Management in Geodise

... Providing Data Management Services for Engineering  Engineering design and optimisation is a computationally intensive process.  Large quantities of data may be generated at different locations with different characteristics. ...
Relational Databases: A Beginners` Guide
Relational Databases: A Beginners` Guide

... A flat file database has just a single table. In some cases, this may be all that’s needed. A relational database, however, can have multiple tables, with – as the name suggests – relationships between them. This allows you to record information about multiple types of entity, and to show how these ...
A Handy New SAS® Tool for Comparing Dynamic Datasets
A Handy New SAS® Tool for Comparing Dynamic Datasets

... For all file types, SAS also compares the records in both datasets by using the primary key variable specified by the user. If a primary key variable is found in only one file, then SAS flags the record as a discrepancy. Finally, SAS checks for data value differences between variables common to both ...
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... The caCORE SDK is based on a software development paradigm that starts with an abstract model of the entities represented in a particular application. Real-world examples of such entities include identified peptides in an MS2 run or microarray test results. Entities are usually related to other enti ...
MS Access Tour
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The Role of a DBA on an Agile Project
The Role of a DBA on an Agile Project

... etc. should be stored in the same source code repository as the rest of the application code. A stored procedure being checked-in should cause the same continuous integration process to run as would the check-in of any of the application code. As an aside, many database development tasks are done ...
Magic Quadrant for Customer Data-Mining Applications
Magic Quadrant for Customer Data-Mining Applications

... business processes. This demand is impossible to support using traditional “workbench” approaches to data mining. Although an important element in the portfolio of analytical tools that enterprises should establish, these workbenches do not provide the business context for many analyses that enterpr ...
Innovative hyper-converged data center solutions from Dell, Pluribus
Innovative hyper-converged data center solutions from Dell, Pluribus

... many organizations. However, today’s enterprise data center IT infrastructures consist of various hardware and management silos which are limiting the ability of IT organizations to adjust to these business needs and demands quickly and easily. In response, the adoption of hyper-converged systems ha ...
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Lab Guide v1.0 - The Exchange Network
Lab Guide v1.0 - The Exchange Network

... This document walks you through a series of steps of creating a Network Node, a dataflow, two services for data publishing and data submission. At the end of the session, you should have a fully functioning node that actively publishes information from a relational database and is able to accept any ...
API Exposure for Integration
API Exposure for Integration

... The data integration milestone has passed successfully by implementing the Virtuoso Virtual Database. With our capital line-of-business systems running normally, and with local access to their relational engines intact, we have created the all-important unified schema through the Virtuoso VDB. That' ...
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... Tendency and Dispersion  It is important to remember the following facts:  If a nominal scale is used, analysis of data can only be done using modes and frequency distributions.  If ordinal scales are used, analysis of data can be done using medians and ranges (plus modes and frequency distributi ...
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Data Preprocessing Techniques for Data Mining

... 4. Regression: Data can be smoothed by fitting the data to a function, such as with regression. Linear regression involves finding the \best" line to fit two variables, so that one variable can be used to predict the other. Multiple linear regression is an extension of linear regression, where more ...
Spreadsheet Management with the new Office
Spreadsheet Management with the new Office

... enable users to store, analyze, and manipulate data efficiently. They have become ubiquitous in firms for a wide range of activities from financial reporting to securities trading to risk analysis. Unfortunately, this ease of use often causes EUCs to proliferate beyond the reach of governance rules ...
Today`s Network Management Challenges
Today`s Network Management Challenges

... Traditional tools fall short of meeting this new demand, and often only represent the interests of a particular technology expertise or silo of infrastructure. Collaboration is limited and the tools are rarely integrated for a holistic view across technologies. This can impact the length of the busi ...
Data mining tools - Cal State LA
Data mining tools - Cal State LA

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data warehousing - Sayco - Secured Assets Yield Corporation
data warehousing - Sayco - Secured Assets Yield Corporation

... others can access it and perform reporting. Real Time Data Warehouses are data warehouses where it is updated each moment with the influx of new data. For instance, a Real Time Data Warehouse might incorporate data from a Point of Sales system and is updated with each sale that is made. Integrated D ...
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Lost or Stolen Laptop Policy
Lost or Stolen Laptop Policy

... As much as possible, you should access sensitive company data on the company network storage drives rather than storing a copy of the data on your laptop’s hard disk. When off-site, use the company’s (VPN) facilities to access and work on files with sensitive data where applicable. If you absolutely ...
elc 310 day 8
elc 310 day 8

... immediately prior to and after the site.  Third-party, industry-specific sites can also provide information about competitive activities. Company profiles for public firms are available in the SEC’s online EDGAR database + investment firm sites.  User conversation: e-mail lists on every imaginable ...
Informix Red Brick Warehouse
Informix Red Brick Warehouse

... All queries limited to 8k on row size of intermediate and final result tables Important because: • Joining large descriptive columns from the dimension tables to a wide fact table could exceed this limit ...
Peripherals 2 - computing.northampton.ac.uk
Peripherals 2 - computing.northampton.ac.uk

... The main reason we often want to store data or program files that are not in use at a particular time, but we may want to use them later. We need storage methods that do not lose information when the power is turned off. The disk address uses sector and track. The data on a disk is stored in a binar ...
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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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