- Pre-requisite Skills for the course
- Overview of Google Cloud Platform
- Signing up for GCP
- Setup Google Cloud SDK
- Overview of Analytics Services on GCP
- Setup GCS Bucket
- Overview of GCS Web UI
- Overview of gsutil
- Overview of Data Sets
- Manage Files in GCS using gsutil commands
- Copy Retail Data Set to GCS using gsutil commands
- Manage Files in GCS using Python
- Overview of processing data in GCS using Pandas
- Overview of Secrets Manager
- Create Secret using UI
- Managing Secrets using Google Cloud CLI
- Reading Secret Details using Python
- Use Cases of Secrets
- Overview of Cloud SQL
- Setup Postgres Database Server using Cloud SQL
- Configure Network to Connect to Database
- Install PostgreSQL Database Server
- Configure psql CLI
- Connect to Postgres Database using pgAdmin
- Create Database for Retail using Postgres
- Setup Tables and Load Data using Postgres
- Getting Started with Google Big Query
- Overview of Running Queries using Public Data Sets
- Setup Database for Retail in Google Big Query
- Setup Tables and Load Data using Google Big Query
- Compute Daily Product Revenue using Google Big Query
- Create Dimensions and Facts using Google Big Query
- Cumulative Aggregations and Ranking using Google Big Query
- Overview of Google Cloud Functions
- Validate GCS Bucket
- Create Google Cloud Function for Cloud Storage
- Update Requirements for the Project
- Review File Converter Logic
- Deploy File Converter Logic
- Overview of GCP Dataproc
- Setup Single Node Hadoop and Spark Cluster using Dataproc
- Setup Remote Development Environment using VS Code
- Review Data Sets
- Run Spark SQL Commands or Scripts using Dataproc
- Run Pyspark Applications using Dataproc
- Review Spark Jobs on Dataproc using Spark UI
- Overview of Databricks on GCP
- Overview of DBFS
- Mount GCS Buckets on DBFS
- Run Spark SQL Commands or Scripts using Databricks Workflows
- Run Pyspark Applications using Databricks
- Review Spark Jobs on Dataproc using Spark UI