From the course: Data Science on Google Cloud Platform: Exploratory Data Analytics

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Datalab best practices

Datalab best practices - Google Cloud Tutorial

From the course: Data Science on Google Cloud Platform: Exploratory Data Analytics

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Datalab best practices

- [Instructor] Let's review some of the best practices for using Datalab. As an analyst, you might be excited about data and all the insights it brings, but you need to also watch out for all the billing charges that accumulate on the GCP platform. Organize yourself before starting to explore data with Datalab. Ask yourself if the data deserves to be analyzed in GCP. See if downloading data to a laptop might be sufficient to run local analysis. Use source-code control with Android to control code changes and team access. Save intermediate results in BigQuery or Google cloud storage and reuse them. (mumbles) summaries can be saved this way so you don't have to recompute them every time you run the notebook. Watch out again for corresponding costs. When large scale data processing is required for items like booming, creating indicator variables, aggregations et cetera, see if building data flow pipelines is more appropriate than trying to do it through Datalab. You can use Datalab on…

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