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Software Functionality Revealed in Detail
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 data mining implementation


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

data mining implementation  Truth about Data Mining A business intelligence (BI) implementation can be considered two-tiered. The first tier comprises standard reporting, ad hoc reporting, multidimensional analysis, dashboards, scorecards, and alerts. The second tier is more commonly found in organizations that have successfully built a mature first tier. Advanced data analysis through predictive modeling and forecasting defines this tier—in other words, data mining. Data mining has a significantly broad reach and application.

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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

Mining Industry ERP and CMMS RFI/RFP Template

Financials, Human Resources, Manufacturing Management, Process Manufacturing, Inventory Management, Purchasing Management, Quality Management, Sales Management, Project Management, Product Technology, and more 

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Komatsu Employs “Mod Squad” For Logility Implementation


At the Connections 2000 Logility user conference in New Orleans, users recounted implementation stories. Few were as striking as that of the Komatsu’s DRP implementation modifications, a testament to human ingenuity.

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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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Data Quality: Cost or Profit?


Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.

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Best Practices for a Data Warehouse on Oracle Database 11g


Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

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Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

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Rapid Implementation: The New Age of ERP


For midsize firms seeking more value in a shorter period of time, a rapid enterprise resource planning (ERP) implementation may be the way to go. If you’re unsure this is the right choice, you need to consider some important factors. The best candidates tend to be ERP solution first-timers. Learn more about how to work closely with ERP partner vendors for a rapid—and successful—ERP implementation.

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Data Masking: Strengthening Data Privacy and Security


Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

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10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

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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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The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

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