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Optimizing Performance of LookML Queries
  • Level Professional
  • المدة 2 ساعات hours
  • الطبع بواسطة Google Cloud
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عن

This is a Google Cloud Self-Paced Lab. In this lab, you'll learn the best methods to optimize query performance in Looker. Looker is a modern data platform in Google Cloud that you can use to analyze and visualize your data interactively. You can use Looker to do in-depth data analysis, integrate insights across different data sources, build actionable data-driven workflows, and create custom data applications. Big, complex queries can be costly, and running them repeatedly strains your database, thereby reducing performance. Ideally, you want to avoid re-running massive queries if nothing has changed, and instead, append new data to existing results to reduce repetitive requests. Although there are many ways to optimize performance of LookML queries, this lab focuses on the most commonly used methods to optimize query performance in Looker: persistent derived tables, aggregate awareness, and performantly joining views.

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Optimizing Performance of LookML Queries

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  • Optimizing Performance of LookML Queries

Auto Summary

Discover how to optimize LookML query performance in Looker with this Google Cloud self-paced lab. Ideal for professionals in Big Data and Analytics, learn methods like persistent derived tables, aggregate awareness, and efficient view joins. Taught by Coursera, this 120-minute course offers a practical approach to enhancing data analysis and visualization on Google Cloud. Available under the Starter subscription, this course is perfect for those looking to deepen their skills in data-driven workflows and custom data applications.

Google Cloud Training
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Google Cloud Training