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The Gartner Report
Trillium Software Positioned in Leaders Quadrant in the Magic Quadrant for Data Quality Tools
The Gartner Report ranks businesses in the data quality industry based on their performance in several key categories:
- - Ability to execute, products and services, overall viability, sales execution/pricing, market responsiveness and track record, marketing execution and customer experience
- - Completeness of vision, market understanding, marketing strategy, sales strategy, offering (product) strategy, business model, vertical/industry strategy, innovation and geographic strategy
Leaders in the market demonstrate strength across a complete range of data quality functionality including profiling, parsing, standardization, matching, validation and enrichment.
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Hendrik Doeringer, Manager CCI Customer Intelligence, talks about Canon Europe's solution to improved customer intelligence using technology from Oracle and Trillium Software.
A recorded webinar is available, login in and view it here.
| Oracle Customer Data Hub : | Trillium Software for Oracle :
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Today, the Trillium Software System validates, updates and qualifies customer and address data either overnight, when other systems submit the information in batch runs, or in real-time when customer data is first entered.
When Porsche or its subsidiaries or dealerships search for a customer in mySAP CRM, the Trillium Software System acts almost invisibly to ensure a full and accurate record is presented. Millions of records are searched in less than a second. pdf
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Incorporating an effective data quality solution into your project requires a number of additional activities throughout the lifecycle of your project plan. Some tasks are more suited for business user resources to take the lead on while other tasks are primarily technical activities.
This white paper introduces some of the techniques used by successful companies to plan and successfully implement data quality processes as part of an initiative. While technology greatly facilitates and automates data quality management, it should be applied in accordance with a measurable, objective methodology to assure success and a high ROI for the project. As you’ll see in the pages to follow, process, people, and business expertise are major components in achieving an improvement in data quality, leaving technology as a way to automate and improve processes.
Open the whitepaper here
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An organization’s master data may well be its most valuable set of assets. Its product lines, its customers, its suppliers and partners, its inventory and materi-als—all this information adds up to unique and proprietary business information. To achieve master data, however, requires resolving some tough data quality is-sues involving massive volumes of data within a business environment where changing data is the only constant. Open the whitepaper here |
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