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Data Integration and Quality - White Papers

See the most recent data integration and quality whitepapers below.

Find out more about how your organization can post a paper.


Demand and Sales Funnel Analytics—How Forward-Thinking Marketing Organizations Deliver Competitive Differentiators

Demand and Sales Funnel Analytics—How Forward-Thinking Marketing Organizations Deliver Competitive Differentiators

03/10/10

Designed for the marketing operations manager and executive, this series of Sirius Decisions research briefs focuses on the emergence of Marketing Operations and its increasing adoption of demand and sales funnel analytics to drive best-in-class performance and deliver competitive differentiators.


Sales Intelligence

Sales Intelligence

03/10/10

Examines the benefits of incorporating sales intelligence into the early portion of the sales cycle. For example, VITAS has been using IBM Cognos TM1 for over 10 years for everything from complex expansion planning to health-care regulatory compliance, realizing numerous benefits. Read how in this case study.


Data-Driven Marketing

Data-Driven Marketing

03/10/10

This report examines how organizations are using data to impact marketing performance and marketing effectiveness. For example, VITAS has been using IBM Cognos TM1 for over 10 years for everything from complex expansion planning to health care regulatory compliance, realizing numerous benefits. Read how in this case study.


Creating a Single Customer View: The Importance of Data Quality for CRM

Creating a Single Customer View: The Importance of Data Quality for CRM

03/04/10

Effective CRM demands the creation of a single, complete, accurate view of customer information that includes purchasing history, product interest, and recent support interactions. Competitive companies leverage single, trusted views of customers to drive improvements in product positioning, customer service and support, customer retention and life-time value. In today’s connected world, customer information degrades rapidly. Enterprises require a data quality solution able to profile and discover data anomalies and issues, correct and standardize all types of data, and maintain data accuracy and consistency in real time.


Data Quality Essentials: A Project Manager’s Guide to Data Quality

Data Quality Essentials: A Project Manager’s Guide to Data Quality

03/04/10

Any data intensive project offers an opportunity to improve data quality. Initiatives ranging from CRM, MDM, ERP, Business Intelligence, data warehouse, data governance, and any data migration, consolidation, or harmonization endeavor warrant a closer look at the quality of the data that will populate the target application or system. To provide a roadmap for optimal effectiveness and coordination, we offer a detailed guide that identifies, for business team members and IT resources, the data quality- related tasks that should be incorporated into a project plan. These data quality essentials emanate from best practices gathered from field experience resulting from thousands of data management projects and successes.


An Architecture for Software-as-a-Service (SaaS) Business Intelligence

An Architecture for Software-as-a-Service (SaaS) Business Intelligence

03/03/10

This white paper discusses how companies are exploring and successfully implementing SaaS to support on-demand business intelligence across all levels of their enterprise


Addressing the Destructive Business Impact of Data Performance Problems

Addressing the Destructive Business Impact of Data Performance Problems

02/04/10

Accelerate your current data integration environment and eliminate the processing bottlenecks and data latencies caused by exponentially growing data and shortened operational timeframes. This white paper offers a cost-effective, scalable, and efficient alternative to traditional and costly Band-Aids like adding expensive hardware, custom-coding, and the “rip-and-replace” approach. Learn how to optimize your DI environment and: • Increase revenue opportunities • Decrease costs • Improve decision-making • Secure customer retention


Lessons Learned: Survey of Financial Services Companies Uncovers Data Governance Trends

Lessons Learned: Survey of Financial Services Companies Uncovers Data Governance Trends

01/26/10

In the summer of 2009, DataFlux conducted a survey to understand data management trends in the financial services industry. The research examined how this industry is approaching managing its data, the breadth and depth of data governance in this sector, what motivates data management strategies, and what kind of rules the industry thinks should be introduced in the future to promote success.