Data Quality Basics

Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue.

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VoIP Introduction

VoIP uses internet protocol data packets to transfer voice, fax, and other data over the shared network, rather than the traditional public switched telephone network (PSTN), which is based on copper wires carrying analog voice data over the dedicated circuits. VoIP, in contrast to PSTN, uses what is called packet-switched telephony, whereby the voice information travels to its destination in individual network packets across the Internet that are assembled and then converted to voice. Learn the... Read More

Self Service Business Intelligence

Self service BI is technology that provides non-technical individuals who need data with the ability to gather and display meaningful information. The technical and business complexities of identifying data sources, transforming and integrating data sets, enhancing data quality, and providing a data repository are necessarily addressed before a self service BI application is made available. Read this white paper to learn more about how the technical framework and infrastructure for supporting self... Read More

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VoIP Introduction

VoIP uses internet protocol data packets to transfer voice, fax, and other data over the shared network, rather than the traditional public switched telephone network (PSTN), which is based on copper wires carrying analog voice data over the dedicated circuits. VoIP, in contrast to PSTN, uses what is called packet-switched telephony, whereby the voice information travels to its destination in individual network packets across the Internet that are assembled and then converted to voice. Learn the... Read More

Data Quality Trends and Adoption

While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More

Overall Approach to Data Quality ROI

  • Source: SAP
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Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More
 
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