Home
 > Research and Reports > White Papers > Developing a Universal Approach to Cleansing Customer...

Developing a Universal Approach to Cleansing Customer and Product Data

Source: SAP
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.


Featured publications:

Comparing the Total Cost of Ownership of Business Intelligence Solutions
Source: Birst For many companies, traditional business intelligence (BI) software is costly and resource-intensive. So are open source alternatives that require significant configuration and integration. In contrast, software-as-a-service (SaaS) solutions can reduce the cost of a BI deployment by providing automation and pre-integration. Compare total cost of ownership (TCO) for traditional, open source, and SaaS BI solutions. Read More...
11 Criteria for Selecting the Best ERP System Replacement
Source: Epicor An enterprise resource planning (ERP) system is your information backbone, reaching into all areas of your business and value chain. That’s why replacing it can open unlimited business opportunities. The cornerstone of this effort is finding the right partner. And since your long-term business strategy will shape your selection, it’s critical that your ERP provider be part of your vision. Read More...
Measure, Analyze, and Manage: Optimizing Marketing Results with Business Analytics
Source: IBM By adopting a data-driven approach that incorporates business intelligence (BI), predictive analytics and performance management capabilities, marketing executives can empower their teams to measure, analyze, and manage marketing efforts for greater effectiveness and contribution to top line revenue growth. These advanced analytics techniques help marketers harness all of their data, detect patterns of customer behavior, and acquire a deeper understanding of customers as individuals — ultimately leading to new methods of personalized engagement. Read More...


You may also be interested in these related documents:

Scalable Data Quality: A Seven-step Plan for Any Size Organization
Source: Melissa Data 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. Read More...
Optimizing Gross Margin over Continously Cleansed Data
Source: epaCUBE 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. Read More...
Four Critical Success Factors to Cleansing Data
Source: PM ATLAS Business Group, LLC Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology. Read More...

 
comments powered by Disqus



Recent Searches
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Others

©2014 Technology Evaluation Centers Inc. All rights reserved.