Join Kumaran Ponnambalam for an in-depth discussion in this video Next steps, part of Data Science on Google Cloud Platform: Exploratory Data Analytics.
- [Instructor] Now that you have taken this course,…you can take your learning even further.…Learn about how to build the other stages…of data science on GCP, namely data storage,…building data pipelines, and predictive analytics.…Explore other exploratory data analytics options in GCP…including data studio and cloud data float.…Build and implement life project…for data science on GCP.…Data always intrigues me.…
I bet it intrigues you too.…So let's keep exploring it and find better ways…of extracting knowledge out of it.…
Author
Kumaran Ponnambalam
Released
11/14/2018- Setting up Cloud DataLlb for exploratory data analytics
- Segmentation and profiling
- Reading and writing data from BigQuery
- Managing cloud storage buckets
- Creating visualizations of BigQuery data with the GCP Charting API
- Managing Datalab instances
Skill Level Intermediate
Duration
Views
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Introduction
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Why EDA on Datalab?1m 2s
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Data science modules covered2m 11s
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1. Exploration Options in GCP
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BigQuery2m 32s
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Datalab2m 14s
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Data Studio2m 10s
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Cloud Dataflow2m 17s
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2. Cloud Datalab Basics
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What is Datalab?1m 3s
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Setting up the Cloud SDK3m 11s
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Setting up Datalab3m 3s
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Managing Datalab2m 12s
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Using the exercise files1m 12s
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3. Datalab: BigQuery
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Setting up BigQuery3m 15s
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BigQuery commands1m 36s
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Reading data from BigQuery1m 13s
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Working with DataFrames1m 29s
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Writing data to BigQuery1m 30s
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4. Datalab: Cloud Storage
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Listing bucket contents2m 38s
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Managing buckets1m 18s
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Writing to buckets1m 26s
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5. Datalab: Visualizations
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6. EDA with GCP: Use Case
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Statistics and correlations1m 37s
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Segmentation and profiling1m 15s
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7. Managing Datalab
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Datalab instance management1m 13s
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Adding new packages1m 8s
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Managing source code1m 16s
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Datalab best practices1m 17s
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Conclusion
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Next steps42s
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Video: Next steps