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Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

application in data mining  predefined range. In addition, application interfaces must provide constrained input fields in order to simplify data capture for the user, as well as enforce business rules. For instance, North American telephone numbers must be constrained to 10 digits, gender entered through a constrained user interface, and so on. Consistency across business systems . A unified approach to building organization-wide application systems is paramount to ensure that entities are described consistently across multiple Read More

Business Intelligence (BI)
Business intelligence (BI) and performance management applications enable real-time, interactive access, analysis, and manipulation of mission-critical corporate information. These applications pro...
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Documents related to » application in data mining


Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

application in data mining  Management , Data Management Application , Performance Data Management . Contents   The data deluge Businesses, governments and society are only starting to tap its vast potential Data, data everywhere Information has gone from scarce to superabundant. That brings huge new benefits, says Kenneth Cukier—but also big headaches All too much Monstrous amounts of data A different game Information is transforming traditional businesses Show me New ways of visualising data Needle in a haystack The uses of Read More
Enterprise Application Provider May Deepen Market Impact
The worst is past for SoftBrands. However, the vendor must still deal with the problem of blending many formerly independent organizations together, while

application in data mining  scale by building common application components as commodities that can be deployed within the entire product portfolio is tempting and promising in the very long run. However, the flagship back-office product lines will likely remain on separate tracks for some time to come, owing to their quite disparate, and in some instances proprietary, technologies and user bases. The disparity in the technological foundation of the products is also a disadvantage in that it has likely multiplied development Read More
The Truth about Data Mining
It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data

application in data mining  significantly broad reach and application. It can be applied in any situation where it is necessary to discover potential knowledge from vast amounts of data. Throughout this article, the word knowledge is used to refer to meaningful patterns derived through techniques in data mining that can stimulate an organization's goals (such as company revenue, Web site traffic, increase in crop yield, and improved health care). The field of data mining brings together techniques from statistics; machine learning Read More
Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a

application in data mining  our CRM solutions and application products. OLE DB for Data Mining has been under vendor review and modification since its introduction last May at Tech*Ed '99 and now incorporates the Predictive Model Markup Language (PMML) standards from the Data Mining Group, an industry consortium that facilitates the creation of useful standards for the data mining community. PMML is an XML-based language that provides a quick and easy way for organizations to define and share data mining models between compliant Read More
A Roadmap to Data Migration Success
Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources,

application in data mining  data migration sql,data migration strategies,data migration framework,server data migration,data migration issues,erp data migration,data migration validation,data migration test plan,data migration solutions,data migration strategy document,data migration companies,data migration testing strategy,data migration sql server,data migration planning,data migration plan example Read More
The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers
The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to

application in data mining  Rack-oriented cooling will find application in situations where extreme densities, high granularity of deployment, or unstructured layout are the key drivers. Room-oriented cooling will remain an effective approach for low density applications and applications where change is infrequent. For most users with newer high density server technologies, row-oriented cooling will provide the best balance of high predictability, high power density, and adaptability, at the best overall TCO. About the Authors: Read More
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a

application in data mining  data structures of each application and business unit have not been taken into account, as they were developed independently of one another. This means that data may be captured in different ways. For example, customer address information and name may be recorded in different formats within different business units. When data is pulled from one system to another, this particular customer information may not be synchronized. CDI and Data Integration CDI represents a consolidated view of customer data. Read More
PeopleSoft Delivers Oxymoron In 'Supply Chain in a Box'
Users would do well to take PeopleSoft’s claims with a vein of salt and maintain realistic expectations regarding the challenges they will face in integrating

application in data mining  term, but only proven application of its supply chain solutions will enable the vendor to contend on an equal footing with SAP, J.D. Edwards, and Oracle. User Recommendations We are sure that there are small organizations with simple supply chains for which the product might well run out of the box. But in general, users would do well to take PeopleSoft's claims with a vein of salt and maintain realistic expectations regarding the challenges they will face in integrating their supply chains. Don't buy Read More
Why Demandware Is Out in Front in the Digital Commerce Sector
Whether you call it e-commerce, e-retailing, digital commerce, or something else entirely, there is a veritable revolution going on in the internet commerce

application in data mining  Demandware Is Out in Front in the Digital Commerce Sector Whether you call it e-commerce, e-retailing, digital commerce, or something else entirely, there is a veritable revolution going on in the internet commerce space. While consumers continue to seek and expect near-perfection in the digital commerce experience, vendors have been struggling to deliver what should be a seamless experience across channels. Demandware has been particularly assertive about tackling this, developing from a SaaS newcomer Read More
Business Basics: Unscrubbed Data Is Poisonous Data
Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data

application in data mining  Quality Control Every business application should be periodically assessed for data quality. It should be a quarterly effort to assure reliable processing and to maintain the value of business decisions made from data. Software tools such as Carleton's Passport , Prism Software Solutions' Warehouse Manager , QDB Solutions' Analyze , and Vality Technology's Integrity can be purchased, or homemade tools can be built to examine data fields and relationships. Data should be managed as a corporate asset that Read More
The New Virtual Data Centre
Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business

application in data mining  Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. Read More
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

application in data mining  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More
Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and

application in data mining  data warehouse,data warehouse architecture,data warehouse concepts,data warehouse software,data warehousing analysis,data warehouse community,data warehouse automation,data warehousing olap Read More
Data Center Projects: Project Management
In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined

application in data mining  Center Projects: Project Management Data Center Projects: Project Management If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today's always on, always available world where businesses can't stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power problems and temperature. As a global leader in Read More

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