Defining what “good” data means is not a trivial exercise. The lack of a shared understanding across the business can result in costly data quality failures and create real friction between teams that produce, manage and consume data. Since the definition is different for different people, neither the most expensive enterprise tools nor the most sophisticated ML-driven approaches can solve the problem.
By working closely with various data stakeholders across an organization and tying each data element to critical business use cases, we’ll help you create a shared, objective, value-driven understanding of “good”. In addition to creating these Data Stories, we’ll validate Data Dictionaries, execute Deep Data Profiling, conduct a Governance Assessment, develop a Test Plan for Automation and establish a Maintainability Plan with internal data stakeholders.
Rapid onboarding and time-to-value of 100 days or less
Well defined solution strategy with set deliverables
Delivered in multiple sectors and maturity stages
Our cognitively diverse quality engineering teams, 75% of whom are autistic,
combine deep technical skills with an aptitude for rapidly absorbing complex domain
knowledge, so we can hit the ground running.
The Ultranauts team was able to ramp up quickly and get into our organization, seamlessly integrate with our team and understand our business priorities. Ultranauts is unique in terms of their high calibre of quality engineers, and they’ve been able to get the right processes and structure in place to ensure that we can trust the data being brought into our platforms and systems, as well as the outputs being generated by our models on the other end.
EVP Data Science, Insurtech Startup