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White Papers

Channel: Data Quality - Tom Breur RSS Feed for Data Quality - Tom Breur

 

Displaying 1–15 (of 27)

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Title Popularity * Date
Exploring the Use of Social Network Analysis (SNA) in the Telecommunications Industry Summary
This study from Frost & Sullivan discusses how SNA is run in mobile network operators, cable operators and fixed providers; the nature of SNA providers, their business models and approaches; and the market size of this segment from the point of view of SNA providers.

Topics: Business Intelligence, Social Media
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15-07-2010
Social Network Analysis and KSN Summary
The document describes the principles of social network analysis, the existing software solutions (KXEN's KSN and competitors), and their possible applications.

Topics: Analytics, Business Intelligence
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15-07-2010
The Analytics Landscape Summary
This white paper provides an overview of analytic technologies and how Jaspersoft‘s products and ecosystem address those areas.

Topics: Business Intelligence
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15-07-2010
Jaspersoft and the Analytics Landscape Summary
This white paper describes how the Jaspersoft ecosystem provides the most efficient, robust and scalable analytics solution, even as explosions in data accelerate and the market demands ever increasing insight.

Topics: Analytics, Business Intelligence
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15-07-2010
Customer Centricity, Master Data and the 360-Degree View Summary
When reviewing the popular literature on customer data integration and master data management, a frequently recurring business driver is the ability to establish a “360-degree view of the customer.” This concept has turned into the holy grail of comprehensive customer intelligence. This paper provides questions that should be considered and reviewed during any project designed to deliver a 360-degree view. By using these questions for preliminary guidance, one may clearly articulate where the business can derive value, determine performance metrics and thresholds, and improve the chances of success. The paper then explores how information sharing and identity resolution combine to show the connection between MDM and enterprise customer centricity.

Topics: Information Quality (IQ), CRM, Data Quality, Data Warehousing, Master Data Management (MDM), Customer Data Integration
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06-05-2010
Finding an Upside in the Downturn with Data Quality Summary
The current macroeconomic malaise means organizations in almost every sector are finding it tough. Although companies are relying even more on IT systems to run their businesses in a leaner and meaner fashion, new IT investments are invariably impacted as well. CIOs are left scratching their heads on how to sustain and fund important information management projects such as master data management (MDM) and data quality. This paper from Ovum, a leading research firm in technology, telecommunications and other business sectors, describes why a rigorous data quality program is now a business imperative rather than a luxury.

Topics: Information Quality (IQ), Information Management, Data Quality, Master Data Management (MDM), Data Governance, Data Management
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06-05-2010
A Guide to the Value of Reliable Data in Insurance Summary
How critical is reliable data to the insurance industry? Insurance companies must attract the right customers, price correctly, write the right business, decline high-risk business, mitigate risk and reserve correctly. They must also maintain positive cash flow, manage outstanding claims and get the best re-insurance deals – all the while minimizing operating expenses. If unreliable data is flowing through the organization, the impact on the core insurance operational and analytical processes can be catastrophic. This white paper from industry thought leader Mike Ferguson looks at the importance of reliable data to the insurance industry, focusing on the impact of poor data. He discusses how an enterprise data quality approach can help get you back control of your data.

Topics: Information Quality (IQ), Data Quality, Data Warehousing, Enterprise Information Management (EIM), Data Management
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06-05-2010
A Guide to the Value of Reliable Data in Retail Banking Summary
This paper by Mike Ferguson of Intelligent Business Strategies examines the impact of unreliable data on retail banks. Defining the requirements needed to guarantee data reliability in retail banking, it offers a practical approach to creating and governing that data, and shows how you can get started in making trusted data available in to help improve marketing, customer service, risk management, compliance and profitability.

Topics: Information Quality (IQ), Information Management, Data Quality, Data Governance, Data Management
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06-05-2010
Who Ensures Clean, Consistent Data? (Hint: It’s Not Just IT) Summary
Inaccurate customer data costs businesses a staggering $611 billion annually. This TDWI report explores real-world solutions for strengthening alliances between business and IT, investing in technology that corrects data at its entry source, and solving data accuracy and standardization issues.

Topics: Information Quality (IQ), Business Intelligence, Data Quality, Data Warehousing, Data Profiling, Data Stewardship, Business Analytics
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27-04-2010
The State of Data Summary
This series of insightful, timely articles strikes at the heart of data quality and data integration challenges. Included here is a close look at harnessing the exploding volumes of unstructured and semistructured data, which so many companies are struggling to tame and leverage for true business value.

Topics: Information Quality (IQ), Data Quality, Data Integration, Data Profiling, Data Migration, Data Stewardship, Data Management
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29-03-2010
Integrating Content Across the Enterprise: An Introduction to ASG-Total Content Integrator Summary
Research shows that enterprise content is growing by as much as 200% per year, and the risks of not managing it effectively are growing even faster. This paper examines the business and technical challenges of integrating disparate enterprise content and offers an elegant solution to address these issues.

Topics: Data Integration, Compliance, Content Management, Data Modeling and Design, Data Management
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10-03-2010
Avoiding the Integration Tar Pit Summary
If you don’t plan and design the data integration parts of your projects, you are destined for a data integration tar pit, with a tangled mess of point-to-point integrations of exponentially increasing complexity. This Bloor Research on agile integration discusses fast delivery of cost-effective data integration which can respond immediately to changing business needs and which doesn’t grow more complex (and expensive) to manage over time.

Topics: Data Integration, Data Acquisition and Delivery, Data Quality, Metadata, Data Profiling, Data Migration
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08-03-2010
Comparative Costs and Uses of Data Integration Platforms Summary
Bloor Research has set out to discover how data integration platforms are being used in practice. That is, what types of integration tasks they are being used for, on what scale, and whether this differs by product or vendor. Bloor arrived at an estimate of cost effectiveness based on total cost per project.

Topics: Data Integration, Data Quality, Data Warehousing, Open Source BI, ROI (Return On Investment), Data Management
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02-03-2010
The Analytics Revolution: Optimizing Reporting and Analytics to Make Actionable Intelligence Pervasive Summary
By transitioning from an organic evolution of corporate business intelligence and analytics environment built on top of a myriad of technology components to a strategically architected end-to-end solution, your organization can gain a rapid time to value through real-time, integrated analytics, resulting in advantageous intelligence delivered to the appropriate decision makers at the right time.

Topics: Analytics, Data Quality, Data Management
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07-01-2010
Core Data Services: Basic Components for Establishing Business Value Summary
This white paper explores how a consolidated set of value-added data services that span the scope of data management best practices can reduce operational costs, increase efficiency and improve the quality and utility of enterprise data.

Topics: Information Management, Data Quality
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07-01-2010

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