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Enable easy discovery and reuse of existing assets, provide access to usage context to build trust, track (re)use and incremental value.
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How to bring added value to existing assets
What level of trust do the users have in current D&A assets?
What are the long-term impacts and benefits of data analytics?
How frequent is a data asset reused in projects?
What standards are put in place to ensure quality D&A reuse?
Maximize value generated from D&A assets
Shorter time-to-market and fewer risks of error for new projects
Foster D&A culture and data literacy to ease communication
By having access to existing assets, models, API, best practices, templates and more, D&A users can choose suitable initiatives to support use case executions regularly.
The easiness to discover and browse D&A assets avoids the organization from dedicating duplicated efforts in similar D&A asset developments.
Assist users to assess data assets accuracy and educate them to adopt D&A in projects by providing usage guides, documentation and best practices.
Onboard new users and continuously support existing ones to learn how to use D&A initiatives to encourage the use and reuse of them.
Thanks to collaboration across different functions and teams, submission and validation workflows become smoother and more comprehensive.
Govern assets by gathering feedbacks, enable peer review and emphasizing alignment in order to improve existing assets quality.
One of the common challenges in many organizations is that there isn’t a metric to track how often a D&A initiative is used or even to track if an asset is ever used.
By using centralized usage metrics and context, the organization can drive the assets portfolio, roadmap as well as monitor the use & reuse of asset to better manage the knowledge they own.
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