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Data Needs and Infrastructure in AI
Defining data needs is crucial for AI processes. It includes assessing if you have the required data, ensuring its cleanliness, curation, security, and organization. In case of lacking data, acquiring more or better data or changing collection methods might be necessary. Additionally, considerations for unstructured data like video, audio, or semi-structured data with structured metadata need to be made. While in traditional BI, structured or tabular data is common, AI mostly deals with unstructured data, which constitutes about 95% of the world's data.
Artificial intelligence technologies promise to revolutionize business and produce new sources of value. In order to make those promises a reality there is a substantial amount of strategy and investment required. Colleen Tartow has worked across all stages of the data lifecycle, and in this episode she shares her hard-earned wisdom about how to conduct an AI program for your organization.
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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