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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.

data mining definition  Six Steps to Manage Data Quality with SQL Server Integration Services Six Steps to Manage Data Quality with SQL Server Integration Services Source: Melissa Data Document Type: White Paper Description: 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 Read More...
Mining Industry (ERP & CMMS)
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Documents related to » data mining definition


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.

data mining definition  The Truth about Data Mining The Truth about Data Mining Anna Mallikarjunan - June 19, 2009 Read Comments 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 Read More...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

data mining definition  Scalable Data Quality: A Seven-step Plan for Any Size Organization Scalable Data Quality: A Seven-step Plan for Any Size Organization Source: Melissa Data Document Type: White Paper Description: Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor Read More...
Achieving a Successful Data Migration
The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

data mining definition  Achieving a Successful Data Migration Achieving a Successful Data Migration Source: Informatica Document Type: White Paper Description: The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process. Read More...
Evoke Software Releases Axio Data Integration Product
Evoke Software Corporation has announced the release of Axio™, an e-business integration product designed to web-enable multiple different data sources into a unified view of a business. The product has a very intriguing method of metadata scanning, and should have significant market impact.

data mining definition  Evoke Software Releases Axio Data Integration Product Evoke Software Releases Axio Data Integration Product M. Reed - June 27, 2000 Read Comments M. Reed - June 27, 2000 Event Summary Evoke Software has created a new product based on their existing Migration Architect product. It will be known as Axio and is designed to provide rapid e-business integration with existing corporate operational systems, new e-commerce applications, customer relationship management, and/or data warehousing. Axio is designed Read More...
IFS Applications (version 7.5) for ERP for the Mining Industry Certification Report
IFS Applications (version 7.5) is now TEC Certified for online evaluation of enterprise resource planning (ERP) solutions for the mining industry in the ERP Evaluation Center. The certification seal is a valuable indicator for organizations relying on the integrity of TEC research for assistance with their software selection projects. Download this report for product highlights, competitive analysis, product analysis, and in-depth analyst commentary.

data mining definition  IFS Applications (version 7.5) for ERP for the Mining Industry Certification Report IFS Applications (version 7.5) for ERP for the Mining Industry Certification Report Source: Technology Evaluation Centers Document Type: Certification Report Description: IFS Applications (version 7.5) is now TEC Certified for online evaluation of enterprise resource planning (ERP) solutions for the mining industry in the ERP Evaluation Center. The certification seal is a valuable indicator for organizations relying on the Read More...
Data Storage in the Cloud-Can you Afford Not To?
Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

data mining definition  Data Storage in the Cloud—Can you Afford Not To? Data Storage in the Cloud—Can you Afford Not To? Source: Riverbed Technology Document Type: White Paper Description: Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or Read More...
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unispere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses and a discussion of the results.

data mining definition  2013 Big Data Opportunities Survey 2013 Big Data Opportunities Survey Source: SAP Document Type: White Paper Description: While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unispere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested Read More...
The Bottom Line on Bad Customer Data
You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of

data mining definition  Line on Bad Customer Data The Bottom Line on Bad Customer Data Source: Baseline Consulting Document Type: White Paper Description: You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no Read More...
Six Misconceptions about Data Migration
A truly successful data migration project involves not only an understanding of how to migrate the data from a technical standpoint, but an understanding of how that data will be used and its importance to the operation of the enterprise.

data mining definition  Six Misconceptions about Data Migration Six Misconceptions about Data Migration Norma L. Davis - June 23, 2008 Read Comments Originally published February 4th, 2008 As organizations embark on a system implementation, one of the most important and riskiest activities is data migration—the movement of data from the old legacy system to the new system. While the selection, implementation, and operation of an enterprise application for enterprise resource planning (ERP), enterprise asset management (EAM), Read More...
Master Data Management
It’s common to hear that master data management (MDM) projects are difficult to initiate. But pairing up an MDM project with another initiative already on your organization’s priority list might be easier than you think. Find out some of the basics surrounding MDM itself, including what MDM can refer to, as well as how to couple it with other projects that may already have momentum in your organization.

data mining definition  Master Data Management Master Data Management Source: Skura Corp Document Type: White Paper Description: It’s common to hear that master data management (MDM) projects are difficult to initiate. But pairing up an MDM project with another initiative already on your organization’s priority list might be easier than you think. Find out some of the basics surrounding MDM itself, including what MDM can refer to, as well as how to couple it with other projects that may already have momentum in your Read More...

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