Unstructured data is a stream of data that holds tremendous, untapped value. The database industry shifted to accommodate unstructured data sources, but a lack of awareness frustrated these efforts. Only 46% of organizations have made efforts to extract unstructured data’s value, according to an IDC survey. Now, with the rise of generative artificial intelligence, technology and business leaders have another reason for pursuing and surfacing unstructured data. Companies and IT professionals that have pushed themselves forward with unstructured data may find themselves in a better position to take advantage of generative AI.
Matt Labovich, US data, analytics, and AI leader at PwC, states that it’s time for enterprises to step up “management of unstructured data from sources such as IoT, as well as knowledge documents — PowerPoints, text, Excel spreadsheets.” While structured data strategies have traditionally received the majority of attention, Labovich urges organizations to turn attention to the significant role of unstructured data in the advancement of generative AI.
A recent global survey published in MIT Technology Review Insights, underwritten by Databricks, also highlights the importance of generative AI’s new ability to surface and utilize once-hidden data. The ability to capture and pull value from such data is considered more critical than ever, with the majority of technology executives agreeing that data problems are the most likely factor to jeopardize their AI and machine learning goals.
The generative AI era requires a data infrastructure that is flexible, scalable, and efficient. Unifying data platforms for analytics and AI is crucial to enterprise data strategies, according to more than two-thirds of survey respondents. Bringing data owners, analysts, and users into the process from across the business is also key to data success with generative AI.
