One of the most daunting and time-consuming activities for data scientists and data analysts is understanding new and unfamiliar data sets. When given such a new data set, how do you understand its shape and structure? How can you quickly understand its important trends and characteristics? The typical answer is hours of manual querying and exploration, a process many call data archaeology.

This session will show a better way to explore new data sets by letting machine learning do the work for you. In particular, we will showcase how Anomalo simplifies the process of understanding and obtaining insights from Databricks tables — without manual querying. With a few clicks, you can generate comprehensive profiles and powerful visualizations that give immediate insight into your data's key characteristics and trends, as well as its shape and structure. With this approach, very little manual data archaeology is required, and you can quickly get to work on getting value out of the data (rather than just exploring it).

Talk by: Elliot Shmukler and Vicky Andonova

Here’s more to explore: State of Data + AI Report: https://dbricks.co/44i2HBp The Data Team's Guide to the Databricks Lakehouse Platform: https://dbricks.co/46nuDpI

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