Data Science on Google Cloud Platform: Exploratory Data Analytics

Introduction

• Why EDA on Datalab?
• Data science modules covered

1. Exploration Options in GCP

• BigQuery
• Datalab
• Data Studio
• Cloud Dataflow

2. Cloud Datalab Basics

• What is Datalab?
• Setting up the Cloud SDK
• Setting up Datalab
• Managing Datalab
• Using the exercise files
• Other capabilities

3. Datalab: BigQuery

• Setting up BigQuery
• BigQuery commands
• Reading data from BigQuery
• Working with DataFrames
• Writing data to BigQuery

4. Datalab: Cloud Storage

• Listing bucket contents
• Managing buckets
• Reading objects from a bucket
• Writing to buckets

5. Datalab: Visualizations

• Introduction to the charting API
• Line charts with BigQuery data
• Pie charts with BigQuery data
• Time series analysis with Cloud Storage

6. EDA with GCP: Use Case

• Loading data into a DataFrame
• Cleansing and transforming data
• Statistics and correlations
• Segmentation and profiling
• Writing results to Cloud Storage

7. Managing Datalab

• Datalab instance management
• Adding new packages
• Managing source code
• Datalab best practices

Conclusion

• Next steps