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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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Visit the TEC store to compare leading software solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
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 great plains sql data diagram


Business Intelligence
The ability to extract and present information meaningfully is vital for business management. Indeed, business intelligence tools enable companies to make

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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

Outsourcing, IT Infrastructure

The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical types of activities that these providers perform include data center operations; network operations; backup/recovery services, data storage management services; system administration services; end user support of desktop PCs, laptops, and handheld devices; web site, or application hosting, etc.  

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Documents related to » great plains sql data diagram

Metagenix Reverse Engineers Data Into Information


Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

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Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations


While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of "big data" and the use of analytics to mine that data.

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A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

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A Definition of Data Warehousing


There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

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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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Data Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution


There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas.

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A Roadmap to Data Migration Success


Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them.

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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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Optimizing Gross Margin over Continously Cleansed Data


Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.

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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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