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Software Functionality Revealed in Detail
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 data mining and applications


Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses
Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has

data mining and applications  BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

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 provide users with valuable insights into key operating information to quickly identify business problems and opportunities. Users are able to access and leverage vast amounts of information to analyze relationships and understand trends that ultimately support business decisions. These tools prevent the potential loss of knowledge within the enterprise that results from massive information accumulation that is not readily accessible or in a usable form. It is an umbrella term that ties together other closely related data disciplines including data mining, statistical analysis, forecasting, and decision support. 

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Documents related to » data mining and applications

Ask the Experts: Approaches to Data Mining ERP


From one of our readers comes this question: I am a student of IT Management; I have an ERP course and I am supposed to write an article to review new aspects of ERP systems. I’ve decided to explore the reasons for using data mining techniques in ERP systems—and to look at different modules to which these techniques have been applied. I am going to prepare a framework to determine

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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 proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

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Why Database-agnostic Enterprise Applications Are on the Way Out


Middleware agnosticism is the wave of the future, and the database platform is becoming part of the application. It has therefore become increasingly important that vendors of enterprise applications offer a wider range of middleware choices to organizations.

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Applications Giants Bolster Their Pricing Management Capabilities


Previously price management was an overlooked area by vendors because they lacked the native capabilities to meet this need. However, through partnerships and acquisitions, they are creating viable products, which are enabling enterprises to see greater return.

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Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

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10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

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Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

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MSI Data


There are currently no details available for this vendor. However, we are working to update this vendor’s information in our database as soon as possible. Please check back again.

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Data Storage in the Cloud--Can You Afford Not To?


In Data Storage in the Cloud Can You Afford Not To?

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Governance from the Ground Up: Launching Your Data Governance Initiative


Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys.

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