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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.
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 crm data mining


Data Mining: The Brains Behind eCRM
Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data

crm data mining  what those customers wanted. CRM has been a vital information industry segment for many years, but the special needs of Internet businesses for real-time processing of huge volumes of data led to the creation of a flock of startups and the coining of the term eCRM to describe their niche. Some of the special characteristics of eCRM were that it primarily served (and was offered by) dot-com businesses, that it tended to be weak on the traditional kinds of CRM processing, and that it made effective uses

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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

CRM for Financial and Insurance Markets

Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or in the field). The company can then use this data for specific business purposes by taking a customer-centric rather than a product-centric approach. CRM applications are front-end tools designed to facilitate the capture, consolidation, analysis, and enterprise-wide dissemination of data from existing and potential customers. This process occurs throughout the marketing, sales, and service stages, with the objective of better understanding one’s customers and anticipating their interest in an enterprise’s products or services.  

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Documents related to » crm data mining

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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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 extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right choices about when to restrict the flow of data, and when to encourage it. Find out more.

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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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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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CRM: Big is Not Always the Best


Customer relationship management (CRM) solutions can range from simple contact managers (for a few hundred dollars) to multimillion-dollar enterprise applications that take years to implement. This is why over-buying a CRM system can be one of the most costly mistakes a company can make. But where should you start your research? And what steps should you take after that?

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Agile Data Masking: Mitigate the Threat of Data Loss Prevention


You may not be as protected from data loss as you think. This infographic looks at some ways in which an enterprise's data can be compromised and vulnerable to security breaches and data loss, and shows how data masking can mean lower security risk and increased defense against data leaks.

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Reinventing Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud


Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside of production environments is crucial. Multiple copies of data and constant transmission of sensitive information stream back and forth across your organization. As information shifts between software development, testing, analysis, and reporting departments, a large "surface area of risk" is created. This area of risk increases even more when sensitive information is sent into public or hybrid clouds. Traditional data masking methods protect information, but don’t have the capability to respond to different application updates. Traditional masking also affects analysis as sensitive data isn’t usually used in these processes. This means that analytics are often performed with artificially generated data, which can yield inaccurate results.

In this white paper, read a comprehensive overview of Delphix Agile Masking, a new security solution that goes far beyond the limitations of traditional masking solutions. Learn how Delphix Agile Masking can reduce your organization’s surface area risk by 90%. By using patented data masking methods, Delphix Agile Masking secures data across all application lifecycle environments, providing a dynamic masking solution for production systems and persistent masking in non-production environments. Delphix’s Virtual Data Platform eliminates distribution challenges through their virtual data delivery system, meaning your data can be remotely synchronized, consolidated, and takes up less space overall. Read detailed scenarios on how Delphix Agile Data Masking can benefit your data security with end-to-end masking, selective masking, and dynamic masking.

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Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

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Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

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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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