Data harvesting superapp says LLM tamed its unruly data

Companies are drowning in a sea of information, struggling to navigate through countless datasets to uncover valuable insights. At Grab, we faced a similar challenge.

At Grab, we faced a significant hurdle locating the most suitable dataset for our Grabber's use cases promptly. This challenge stemmed from managing over 200,000 tables in our data lake.

While our in-house tool Hubble excelled at providing metadata for known datasets, it struggled with true data discovery due to its reliance on Elasticsearch.

Eighteen percent of searches were abandoned by staff users at Grab, as the Elasticsearch parameters provided by Datahub failed to yield helpful results.

Read at Theregister