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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.
business data quality,customer data quality,data quality,data quality center,data quality control,data quality improvement,data quality analysis,data quality articles,data quality assessment
Data Quality: A Survival Guide for Marketing
The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an enterprise information management (EIM) system can help.
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Outsourcing, IT Infrastructure
The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical type...
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Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.
data warehouse,data warehouse architecture,data warehouse concepts,data warehouse software,data warehousing analysis,data warehouse community,data warehouse automation,data warehousing olap
Developing a Universal Approach 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.
product data,product data management,pdm,find product data,looking for product data,managing product data,product data sheets,product data sheets available,highlighted product number,model for data exchange,download product data
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.
data quality solution,enterprise information management,enterprise information management strategy,enterprise information management definition,enterprise information management framework,enterprise information management software,data quality maturity,data quality software,open source data quality software,data quality,data quality tools,customer data quality,data quality metrics,data quality management,data quality objectives
Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond
For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.
data migration,data migration management,data migration tools,data migration software,data migration plan,data migration tool,data migration services,data migration best practices,data migration process,data migration testing,crm data migration manager,data migration manager,data migration plan template,sql server data migration,legacy data migration
Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...
implementing energy efficient data centers,implementing,energy,efficient,data,centers,energy efficient data centers,implementing efficient data centers,implementing energy data centers,implementing energy efficient centers,implementing energy efficient data.
Ask the Experts: Approaches to Data Mining ERP
From one of our readers comes this question: I am a student of IT Management; I have an ERP course and I am supposed to write an article to review new aspects of ERP systems. I’ve decided to explore the reasons for using data mining techniques in ERP systems—and to look at different modules to which these techniques have been applied. <!--more-->I am going to prepare a framework to determine
Data Quality: Cost or Profit?
Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.
business intelligence architecture,business intelligence data warehouse,change data capture,customer data,customer data integration,data cleaning,data cleaning software,data cleansing,data cleansing data,data cleansing definition,data cleansing service,data cleansing services,data cleansing software,data cleansing solution,data cleansing solutions
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.
Master Data Management,MDM,Customer Data Integration,CDI,Data Integration,CRM,BI,business intelligence,data standardization,data consolidation,Customer Relationship Management
How to Use Data Management Successfully
Find out in the white paper master data management: extracting value from your most important intangible asset.
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