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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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 generate test data


SaaS-based Test Management
Organizations must keep up with technology and adapt their quality assurance (QA) processes for continued success. Test management isn’t optional. The proper

generate test data  spending valuable time to generate various reports. Qmetry supports installed version as well as hosted instance. The hosted instance enables easy access from multiple locations, meanwhile eliminating installation & support dilemmas as well as backup of test assets. For larger projects an installed version is available. The product utilizes a dashboard which has real-time updates and quality metrics, keeping everyone on the team up to date with the project. In addition, Qmetry offers version control,

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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

Software Test Tools

Tools exist to support software testing at all stages of a project. Some vendors offer an integrated suite that will support testing and development throughout a project's life, from gathering requirements to supporting the live system. Some vendors concentrate on a single part of that life cycle. The software test tools knowledge base provides functional criteria you might expect from a testing tool, the infrastructure that supports the tool, and an idea of the market position of the vendor.  

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Four Critical Success Factors to Cleansing Data


Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

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A Guide to Software Test Tools


Testing a system well is harder than building it. In the face of new risks introduced by the ever-increasing complexity of software and hardware, test tools may be your only practical way to be confident that you've got just what you paid for. From gathering the initial requirements to supporting the system after it has been deployed, test tools are available to support all phases of a project. This article looks at the ways that test tools can be used to design, code, and (of course) test a system.

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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. Consequently, data mining technology becomes important. Here is a framework to help understand the data mining process.

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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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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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Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

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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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Generate Better Leads for Better Sales Results


In the featured white paper generate better leads for better sales results, CSO insights describes how you can produce better quality leads, result...

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Master Data Management: Extracting Value from Your Most Important Intangible Asset


In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe that they are using master data, when in fact what they are relying on is data that is dispersed throughout the enterprise. Discover the importance of master data and how the ideal master data management (MDM) solution can help your business get it under control.

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Data Pro Accounting Software


Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX.

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