TDWI Insight Accelerator | Adopting a Platform Approach for Gaining Insights from Unstructured Data
May 30, 2025
Data practitioners want to take advantage of emerging AI techniques, but they need access to quality data of diverse types that comes from across a distributed environment.
Unstructured data, for example, is critical for supporting new AI use cases, but its very nature —its large volume, diverse formats, and lack of predefined schema—can make it difficult for data engineers to deal with. It is often difficult to govern because it’s spread across a siloed, disparate, and distributed data landscape.
If organizations want to adopt emergent technologies such as LLMs and generative AI, data practitioners should focus on eliminating barriers to success caused by analytics landscapes that have evolved across a disparate array of platforms and distributed systems.
This TDWI Insight Accelerator considers the challenges that organizations are facing with diverse, distributed data types and explores techniques and approaches that can help data engineers overcome these issues.