Finworks Data Fabric

 

Overview

Customers across sectors are benefitting from using the Finworks Data Fabric platform to power strategic, data-driven services critical to their organisation’s mission.

Finworks Data Fabric ensures your data is fit and ready to use when and where it is needed and in the correct form for onward consumption.

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How have we overcome data challenges for clients?

 

Many companies are not aware of how to maximise the potential of their data assets. They find it difficult to unify all their data sources under one banner. Our clients want a data management solution that actually fits their business and their current resources.

 

Our Data Discovery feature allows clients to use all data sources, even pre-existing ones, with their current models without risk. Finworks Data Fabric automates data feeds using workflow, and creates usable data quality rules without the need for development, to make it simple to apply data quality rules or data transformations.

Critical Success Factors

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The metadata capabilities of Finworks Data Fabric which go beyond record keeping and traceability, allowing organisations to accumulate and curate a growing capital stock of knowledge and data assets relevant to the organisation’s targets of interest.

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Ongoing trust in the solution based on the level of automation and consistency that can be achieved at every stage of the data/knowledge value chain from acquisition quality assurance and enrichments to exploitation, publication and distribution.

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The open and flexible nature of the Finworks Data Fabric architecture that allows seamless integration into the broader enterprise technical library of proprietary in-house and third-party components.

 

Unlock the Full Value of your Strategic Data Resources

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Collection and Accessibility – Getting the data you need in a form your teams and systems can use

Data capture that your current ETL cannot handle

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Leave data in situ and extract on demand

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Composes consistent views from many sources

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Creates harmonised data collections 

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Automates data collection to free up resource

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Assurance and Traceability – Making trusted data fit for purpose

Automates quality assurance of data with minimal need for human intervention

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Ensures all data is traceable with a clear data provenance record

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Uses smart business rules to ensure data is consistent with real world requirements 

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Allows data to be used for different purposes but quality assured only once 

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Consistency and Accuracy of Meaning – Ensuring accurate and consistent data meaning

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Ensures data is understood correctly by augmenting and enhancing your metadata records and the processes that maintain them

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Ensures meanings are consistent across different data sets 

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Makes it easier to find and analyse relevant data from a growing set of data assets 

Connection and Integration – Sustainable added value from data

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Make it easier to access data through well-governed automated data publications

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Allows access to data publications through the best channels and tools for each decision-making, analytics or data integration task

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Provides metadata driven assistance for data integration and data selection