Ready your data for generative AI
Drive value with structured, connected data
Data is the key to a successful GenAI solution
The adage — bad data in, bad data out — couldn’t be any truer for generative AI. In fact, the most common mistake in designing and building an AI system is failing to source reliable data to power trustworthy and unbiased models and outcomes.
Our experts identify and map an enterprise’s data landscape, considering where data comes from and how it is stored. We establish clear-eyed data strategies that lay out how to collaborate to make the best business use of data.
how kyndryl helps
Integrate diverse data sources with quality measures for reliable AI operations
You have questions. We have answers.
Data readiness refers to the state and quality of data used to support business processes in an organization. Key aspects of data readiness include data accuracy, completeness, timeliness, consistency, and accessibility. Data readiness is crucial because the ability to derive actionable insights from data is a competitive advantage in today’s data-driven business landscape.
Data can easily be considered an enterprise’s most valuable resource. Data readiness is important because the ability to leverage data is essential to an organization’s success. Data readiness can provide companies with a competitive edge by allowing them to swiftly adapt to changes in the market.
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