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Most organizations have failed to achieve the value of predictive analytics. Typical data science workflows are resource intensive and the data environments within many companies are messy. Data required for analysis can be strewn across so many tools and departments, that data scientists must spend most of their time (60%) preparing data for their analysis, rather than performing the analysis itself.

Join us for this webcast where Kiran Shenoy, with Google Cloud and Looker data science expert Sebastien Fabri, will show you how you can leverage Looker with the power of BigQuery Machine Learning (BQML) to build machine learning (ML) models directly where your data lives.

You will learn how you can:

  • Simplify adoption and deployment of ML with BQML. Kiran will showcase real life customer use cases.
  • Reduce wait-time, operationalize workloads, and reduce complexity for quicker model development.
  • Leverage Looker to write the correct, performant SQL for you making it easy to handle hierarchical data.
  • Eliminate the need to move the data to another data science environment for certain types of predictive models.


Here are the important details:

Webinar Date: Thursday, April 25
When: 10:00 am GMT
Duration: 45 minutes

Presenters

Diane Stetche
Title

Frank Bien
Title

LLoyd Tabb
Title

Diane Stetche
Title

Kiran Shenoy
Google Cloud
Customer Engineer

Sebastien Fabri
Looker
Senior Data Analyst

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About Looker:
Looker is a new kind of analytics platform that lets everyone in your business make informed decisions - from anywhere. Across industries, today's most data-driven businesses use the Looker platform to do more with their data.