Scyllogis are committed to keeping ourselves at the forefront of technology developments to ensure consistent delivery of business objectives within the Insurance and Reinsurance sectors.
To do this we regularly contribute to the discussion and debate of important industry issues, and publish white papers and articles in the trade press. Additionally through our website Blog we now aim to further these discussions by continuing to add our perspective and opinions to those of the global Insurance community....
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Tuesday, 31 January 2012 |
Conclusion
When coupled with best practices for operational data governance, the synergy of data integration, master data management, and data quality enhances the utilization of data from across the organization and benefits all data consumers. As you consider data integration, data quality, or master data management, recall that the success of each individual set of methods and techniques is greatly enhanced when supported by the others. The stage for successful data repurposing can be set early on in the process by taking some immediate, concrete steps:
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Last Updated ( Wednesday, 01 February 2012 )
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Wednesday, 25 January 2012 |
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Master Data Management for Transparency and Visibility
Data integration establishes availability. This availability is enhanced with transparency and visibility, which are enabled by the techniques that usually comprise an effective master data management practice. Master data management is intended to enable the development of an accurate and reliable view of business entities, common reference data concepts, and the dimensional data that are vital to the operations of the enterprise, among a variety of other potential master data concepts.
Essentially, those data sets that
- Exemplify common data concepts,
- Maintain replicated data elements,
- Are subject to multiple business purposes, and
- Can be used by multiple applications
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Last Updated ( Wednesday, 01 February 2012 )
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Thursday, 19 January 2012 |
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Late last year, I raised this topic through my blog. I would like to continue my thoughts here:
Technical Considerations
The conceptual discussion of each of the techniques demonstrates the value that can be added when there is focus on data reuse. Each of the techniques is enabled by technologies that have been refined and implemented as commonplace tools such as data integration, master data management (MDM), and data quality. While these types of tools may already be established for discrete projects, considering them in the context of enterprise utilization exposes potential for economies of scale across the organization. Many organizations already understand the value of one or more of the key technologies necessary for enterprise data utilization. For example, the key stakeholders in an organization that has implemented a data warehouse will have already invested in data integration and data cleansing tools, while business analysts focusing on customer behavior may have initiated a master data management program for customer data integration.
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Last Updated ( Thursday, 19 January 2012 )
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Wednesday, 14 December 2011 |
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Concluding my thoughts on how to reuse enterprise data...
Transparency and Visibility
Transaction systems are designed to successfully execute business operations, but the transaction data is rarely engineered to support the types of reporting and analysis that business analysts use.
Informed decision-making relies on more comprehensive views of data; these views are materialized through the data marts and other analytical environments populated via a data warehouse. Many business decisions hinge on having a large degree of visibility into the knowledge that resides in both operational and analytical systems. For example, understanding climatic risks is necessary in order to purchase reinsurance. The same holds true for analyses of other commonly-used concepts.
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Last Updated ( Thursday, 19 January 2012 )
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Wednesday, 14 December 2011 |
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Continuing my thoughts on how to reuse enterprise data...
With this growing demand for centralizing data, most organizations have invested significant resources in order to provide accessibility and availability to data, ensure the transparency and visibility of data concepts across the application infrastructure, and to enable trust in the reliability and consistency of the data. These are the three fundamental capabilities to maximize utilization of enterprise data.
The implementation of one of these aspects may be directly related to a specific project, even though there is often little consideration of the general applicability of the techniques to benefit other business processes. Therefore, it is worth reviewing the value proposition of each area of capability within the context of enterprise data utilization.
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Last Updated ( Thursday, 19 January 2012 )
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