Developing a Universal Approach to Cleansing Customer and Product Data

  • Source: SAP
  • Written By:
  • Published:
  • (Originally Published On:) )
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 Software Research:

11 Criteria for Selecting the Best ERP System Replacement

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

Analyzing Big Data: The Path to Competitive Advantage

Big data is different from ordinary database information because of the massive volume, the variety, and the velocity. And the data mix now includes product reviews, video, blogs, tweets, and more. But the biggest current challenge may be to articulate a compelling business case for using big data. Find out how companies in various industries are finding value in the data they have already collected and making it actionable. Read More

You may also be interested in these related documents:

Engineering Change Management 2.0: Better Business Decisions from Intelligent Change Management

Traditionally, change management in product development and engineering has been viewed as a way to control cost and improve efficiencies. But companies are becoming aware that better change can drive top-line benefits—and are developing processes with an eye towards improving speed-to-market. Find out why good change management is becoming more important—and how you can use it as a tool to increase product profitability. 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. Read More

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. Read More
 
comments powered by Disqus