TECH TALK

Now available on-demand!

How to turn unstructured text data into actionable insights at scale

Bill Inman headshot

Bill Inmon

“Father of the Data Warehouse”

David Mariani

Chief Technology Officer, Founder at AtScale

Learn how to leverage textual ETL & the automated dimensional modeling capability of a semantic layer to turn raw textual medical record data into actionable insights for research and advanced medical record analytics. 

Join this session to learn how to use textual ETL and a semantic layer to transform raw text into actionable insights across all of your BI/AI tools like Excel, Power BI, Tableau, Looker, DataRobot, H20, over a live data connection in the likes of Databricks for research and analytics at scale.

Our presenters will walk you through an example of how your company can start to leverage raw, unstructured data to better understand your customers, markets, competition, and your own processes and operations. By applying textual ETL to raw text-based data & modeling in your semantic layer, you will be able to extract insights that help drive research, growth, innovation, and efficiency.

In this Tech Talk

We will dive deep on:

  • Textual ETL and turning unstructured text to a structured format that’s analysis-ready 
  • Automated dimensional modeling capability of a semantic layer
  • Analyzing textual medical records reconstructed into a useful form
  • Making actionable insights accessible in your BI/AI tools of choice
  • Real-life scenario and demonstration of analyzing doctor notes in your AI/BI tools of choice for research and advanced medical record analytics.

Who should watch

AI, BI, and Data leaders (e.g., Chief Data Officers, data scientists, data literacy, business intelligence, and analytics professionals) looking to analyze unstructured data for research and advanced analytics.

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