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Documents related to » data mining consultant


Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. 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 CONSULTANT: 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
9/9/2009 2:32:00 PM

Developing a Universal Approach to Cleansing Customer and Product Data
Developing a Universal Approach to Cleansing Customer and Product Data. Find Free Proposal and Other Solutions to Define Your Acquisition In Relation To Cleansing Customer and Product Data. Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

DATA MINING CONSULTANT: Cleansing Customer and Product Data Developing a Universal Approach to Cleansing Customer and Product Data Source: SAP Document Type: White Paper Description: Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy,
6/1/2009 5:10:00 PM

Achieving a Successful Data Migration
Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for 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 CONSULTANT: 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.
10/27/2006 4:30:00 PM

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 CONSULTANT: 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
6/19/2009

A CRM System Needs A Data Strategy
A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.

DATA MINING CONSULTANT: CRM System Needs A Data Strategy A CRM System Needs A Data Strategy David McNamara - July 3, 2003 Read Comments Introduction An underutilized customer relationship management (CRM) system - or one that cannot match its owner s expectations - will reflect poorly on both the vendor who sold it and the IT manager who authorized the purchase and installed it. Both, however, can help successfully manage such expectations (and add value to their respective roles) by wisely counseling about the strategic
7/3/2003

Yanacocha: A Model Mine in Operations and Mining Management
Achieving operational excellence is fundamental for Yanacocha, the largest gold producer in South America. In 1999, Yanacocha decided it needed an online system linking its principal management areas (operations, maintenance, logistics, finance, and human resources), in order to optimize efficiency in administering its assets. It turned to Mincom Ellipse as its corporate management system, allowing standardization of its operations worldwide.

DATA MINING CONSULTANT: Yanacocha: A Model Mine in Operations and Mining Management Yanacocha: A Model Mine in Operations and Mining Management Source: Mincom Document Type: Case Study Description: Achieving operational excellence is fundamental for Yanacocha, the largest gold producer in South America. In 1999, Yanacocha decided it needed an online system linking its principal management areas (operations, maintenance, logistics, finance, and human resources), in order to optimize efficiency in administering its assets. It
10/17/2006 10:17:00 AM

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 bad data are all offered in this paper.

DATA MINING CONSULTANT: 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
5/25/2005 10:37:00 AM

Protecting Critical Data
The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly.

DATA MINING CONSULTANT: Protecting Critical Data Protecting Critical Data Source: Stonefly Document Type: White Paper Description: The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Protecting Critical Data style= border-width:0px; />   comments powered by Disqus Related Topics:   Data Warehousing,   Database
10/19/2011 6:48:00 PM

Fighting Back: How Product Data Management Can Give You the Competitive Edge
Do you want to have a competitive edge? Read this white paper about Product Data Management (PDM). Canadian manufacturers are getting squeezed. Challenged by a rising Canadian dollar, forced to hold the line on prices in the US market, pressured by customer demand for lower prices, better quality, and quicker service, these manufacturers need a way to retain their competitive edge and increase bottom-line profitability. Find out why product data management (PDM) is a solution you can turn to in these challenging times.

DATA MINING CONSULTANT: Fighting Back: How Product Data Management Can Give You the Competitive Edge Fighting Back: How Product Data Management Can Give You the Competitive Edge Source: Technology Evaluation Centers Document Type: TEC Report Description: Canadian manufacturers are getting squeezed. Challenged by a rising Canadian dollar, forced to hold the line on prices in the US market, pressured by customer demand for lower prices, better quality, and quicker service, these manufacturers need a way to retain their competitive
12/12/2007 10:04:00 AM

Meeting the Challenges of Product Traceability with Automated Data Collection
With a minimum of effort, learn all about Meeting the Challenges of Product Traceability with Automated Data Collection.Download our Free whitepaper and find the Software Information You're Looking for. An effective traceability system involves determining which product and manufacturing process attributes to collect and maintain—and deciding when during the manufacturing process to begin collecting those attributes. Do you begin with raw material attributes from the supplier, at inspection, at assembly, at shipping? Explore the many facets of meeting product traceability challenges using automated data collection.

DATA MINING CONSULTANT: Product Traceability with Automated Data Collection Meeting the Challenges of Product Traceability with Automated Data Collection Source: Radley Corporation Document Type: White Paper Description: An effective traceability system involves determining which product and manufacturing process attributes to collect and maintain—and deciding when during the manufacturing process to begin collecting those attributes. Do you begin with raw material attributes from the supplier, at inspection, at assembly, at
7/21/2009 12:59:00 PM

Data Quality Trends and Adoptions


DATA MINING CONSULTANT: Data Quality Trends and Adoptions Data Quality Trends and Adoptions In today s highly competitive and volatile business climate, data quality (DQ) software is no longer perceived as a nice-to-have. As business pressures increase, more and more midsized and large organizations are looking to DQ solutions to improve operational efficiencies reduce costs and risks improve customer experience and loyalty increase revenue provide data transparency and audit ability achieve greater regulatory compliance In
8/23/2011 11:02:00 AM


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