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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

degree data mining  can help evaluate the degree of expectedness or unexpectedness of results obtained from data mining. The knowledge base is an essential input at all stages of the data mining process. 2. The Data Mining Process Figure 1. Creation of the data mining model. Discussion of the data mining process in this article is centered on modeling and assessment. The data mining model constitutes the core, or the center, of data mining. The first step is the creation of the model through the selection of data relevant Read More...
Mining Industry (ERP & CMMS)
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Documents related to » degree data mining


Oracle Further Orchestrates Its SOA Forays Part Two: Strategy
Oracle's vision of a complete collaborative e-Business solution requires a database strategy, an application server strategy, and an e-business strategy. Will

degree data mining  with a very high degree of scalability and reliability. Indeed, Oracle has always been known for its robust database solutions, and less known for its business applications. The highly acclaimed features of Oracle database include improved database availability, functionality, enhanced security capabilities, and an integrated infrastructure for building BI applications. There are also extensive XML capabilities with Oracle Database 10g ( g standing for grid). It leverages existing relational or Read More...
Progressive IT Management Strategies: The IT manager’s 360-degree view of business
The New CIO Business Leader and Change Management ExpertToday’s chief information officer (CIO) not only has to be knowledgeable about technology, but

degree data mining  • Digital transactions—a high degree of digitization of a firm’s repetitive transactions, particularly sales, customer interaction, and purchasing. • Internet use—more use of Internet architectures for key processes, such as sales force management, employee performance measurement, training, and post-sales customer support. • Firm-wide IT skills—high capability of all employees to use IT effectively. There are strong technical and business skills among IT staff, strong IT skills among Read More...
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

degree data mining  ones with a high degree of accuracy, using rules derived by crunching through billions of transactions. Stolen credit cards are more likely to be used to buy hard liquor than wine, for example, because it is easier to fence. Insurance firms are also good at combining clues to spot suspicious claims: fraudulent claims are more likely to be made on a Monday than a Tuesday, since policyholders who stage accidents tend to assemble friends as false witnesses over the weekend. By combining many such rules, it Read More...
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

degree data mining  score that represents the degree of similarity between two sets of data values. Software that provides fuzzy matching capabilities often has underlying libraries that provide knowledge that cannot be discerned purely from text (or phonetic) similarities. For instance, the knowledge that a developer and programmer must be considered the same job title is required to successfully match job titles that have little or no textual similarity. Most tools also provide the possibility to customize matching Read More...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

degree data mining  applications require the highest degree of protection and availability. For these systems, you should look for a solution that limits the amount of data you might lose, as well as the amount of time it takes to recover when something goes wrong. Risks There are many risks that can threaten your remote data (see Figure 3). First, there is the simple and all-too-often case of someone losing a file or e-mail, usually through human error; it may be through an accidental deletion or a deliberate act by a Read More...
Achieving a Successful Data Migration
The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data

degree data mining  a Successful Data Migration Achieving a Successful Data Migration If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Informatica's data migration solution decreases the risk and minimizes the errors inherent in data migration projects. At the same time, our solution reduces the costs of data migration projects by automating processes, improving business-IT collaboration, and incorporating proven best practices. Source : Informatic Read More...
The Use of Ceiling-Ducted Air Containment in Data Centers
Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center

degree data mining  Use of Ceiling-Ducted Air Containment in Data Centers Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center. Typical approaches include ducting either individual racks or entire hot aisles and may be passive (ducting only) or active (include fans). This paper examines available ducting options and explains how such systems should be deployed and operated. Practical cooling limits are established Read More...
Demystifying Data Science as a Service (DaaS)
With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been

degree data mining  Data Science as a Service (DaaS) With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white Read More...
New Data Protection Strategies
One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased

degree data mining  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More...
The Teradata Database and the Intelligent Expansion of the Data Warehouse
In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role

degree data mining  Teradata Database and the Intelligent Expansion of the Data Warehouse In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Ga Read More...
Eliminating Mining Industry Profitability Killers through a Common Decision Environment
Mining corporations and their operating units are under constant pressure to improve financial performance. Efforts to become financially healthy are hampered

degree data mining  what is mining,mines,drill,coal,sme,drilling,mineral mining,problem solving,decision making,what is decision making,making a decision,minerals and mining,minerals mining,gold mining,data mining Read More...
Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security
Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all

degree data mining  Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. Read More...
Flexible Customer Data Integration Solution Adapts to Your Business Needs
Siperian's master data management and customer data integration (CDI) solutions allow organizations to consolidate, manage, and customize customer-related data.

degree data mining  Customer Data Integration Solution Adapts to Your Business Needs Customer data integration (CDI) has become one of the buzzwords within the master data management (MDM) industry. Although the concept of creating a single organizational view of the customer is noble and desirable, its value should also be justified by organizations. To implement a customer data hub that only creates a centralized view of an organization's customer-related data does not affect a company's bottom line, unless Read More...
Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

degree data mining  etc.) with an unknown degree of accuracy. This can foul up sound decision-making and impair effective customer relationship management (CRM). And, poor source data quality that leads to CRM project failures is one of the leading obstacles for the successful implementation of Master Data Management (MDM) — where the aim is to create, maintain and deliver the most complete and consolidated view from disparate enterprise data. The other major obstacle to creating a successful MDM application is the Read More...

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