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Software Functionality Revealed in Detail
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 why data mining


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

why data mining  retailer can plan production. Why Not OLAP or Statistics? Data mining includes advanced techniques for understanding data that far exceed the capabilities of online analytical processing (OLAP). OLAP tools provide the means to perform multidimensional analysis by using powerful algorithms for aggregating data. While OLAP can help look at the sales of a certain product within a specific region and time period, data mining can discover relationships between various attributes in the data and deduce why

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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

Documents related to » why data mining

Data Mining and Predictive Modeling for Condition-based Maintenance


Today’s military logistics agencies must sustain diverse fleets of costly, complex, and indispensible weapon systems and platforms. Modern predictive maintenance solutions can integrate with existing IT infrastructures to collect and transmit data from various platforms to a centralized condition-based maintenance (CBM) database. Learn more about how these solutions enable better-informed decisions regarding specific maintenance actions.

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Why CRM Is So Hard and What To Do About It: Data is key to making CRM work


Making a CRM investment work is a two-step process that begins with unifying disparate systems by creating and managing standardized, reusable business definitions mapped to the different CRM system schemas throughout the organization.

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The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

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How the Mining Industry Benefits from ERP Systems


Integrated enterprise resource planning software normalizes the reporting requirements for a mining company’s various departments. This article loosely shows the parallels between the operations in a mining company and those of a manufacturer whose product is sold on store shelves.

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Forrester TechRadar Report: Data Security


Data security is not just an IT issue these days but a business imperative, as data volumes explode and it is becoming a Herculean task to protect sensitive data from cybercriminals and prevent privacy infringements. As data volumes continue to rise, the burden of protecting sensitive data and preventing security breaches can be crushing. It is necessary to take a holistic, comprehensive, and long-lasting approach to data security that encompasses people, processes, and technology.

This Forrester TechRadar Data Security report provides a framework for developing a long-term approach to keeping your organization’s information secure. Data breaches and insider threats are becoming more common, and your organization needs to achieve compliance and secure privacy without affecting the bottom line. Most companies are also interested in adopting cloud, mobile, and other technologies, which can complicate data security matters even more.

This comprehensive and in-depth report evaluates 20 of the key traditional and emerging data security technologies. To make the report, Forrester interviewed over 40 experts, customers, and users, and drew from a wealth of analyst experience, insight, and research.

Use this report to get informed about what you need to consider to restrict and strictly enforce access control to data, monitor, and identify abnormal patterns of network or user behavior, block exfiltration of sensitive data, and render successful theft of data harmless.

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Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

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Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

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Data Quality: A Survival Guide for Marketing


Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

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Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics


Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are accurate, trustworthy, and complete.

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Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

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