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Software Functionality Revealed in Detail
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 data mining engineer salary


Challenges of the Future: The Rebirth of Small Independent Retail in America
By any measure, retailers are overwhelming small businesses. More than 95 percent of all retailers have only one store. Almost 90 percent have sales less than

data mining engineer salary  power of customer transaction data and make sense of it, delivering the right information for the right purpose at the right moment. Bob Benham (Bob's Bona Fides) described the opportunity: Information technology saves us money and provides more timely management information to make good decisions. The marketing piece is the big opportunity. We are still underdeveloped in mining that data. The real future power of intelligent POS systems can be found more in the customer tracking benefits than in the

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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 » data mining engineer salary

Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise


While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help.

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Six Steps to Manage Data Quality with SQL Server Integration Services


Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

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Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization


Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches increase, companies must find ways to protect data beyond the perimeter of their businesses. But how do they build a data-defensible architecture that will protect data on an ever-evolving network? The answer: by first developing an in-depth defense strategy.

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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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Managing Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses


To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if managing IT is not your core competence, what are your options? A managed service provider (MSP) can help. Learn about the benefits of outsourcing data center management, and make sure your crucial business applications are always available when you need them.

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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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Mining & Quarrying


Mining is the extraction from the earth of materials used in different human activities (industry, trade, energy production, etc.). There are four major types of materials: precious metals and minerals (gold, diamonds, silver, etc.); materials used to produce energy (coal, uranium, etc.); base metals (copper, iron, etc.); and building materials (stone, sand, gravel) extracted from quarries, which are open-pit mines. There are two major types of activities specific to the mining industry: exploration, which involves the search for materials; and extraction, which is the activity of getting those materials out of the earth.

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Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

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Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

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Acumen Data Systems


Acumen Data Systems provides employee time and attendance systems and software. Its software’s focuses include job tracking, shop floor data collection, and employee scheduling.

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