Datalab Overview Google Professional Data Engineer GCP

It is an interactive tool for large-scale data exploration, analysis, and visualization.
based on the open source Jupyter project.
Cloud Datalab is packaged as a container and run in a VM instance.
uses notebooks instead of the text files containing code.
Notebooks combines code, documentation written as markdown, and the results of code execution
notebooks help you write code: execute in interactive and iterative manner and rendering the results
Can share notebook with team members
Import from flat file, databases, or distributed storage systems
Locate and remove or modify missing or mismatched data
Unnest complex data structures
Identify statistical outliers in data for review and management
Perform lookups from one dataset into another reference dataset
Aggregate columnar data using a variety of aggregation functions
Normalize column values for more consistent usage and statistical modeling
Merge datasets with joins
Append one dataset to another through union operations
notebooks can be stored in Google Cloud Source Repository, a git repository.
git repository is cloned onto persistent disk attached to the VM.
Notebooks automatically saved to persistent disk periodically
Do not delete the persistent disk.
VM used for running Cloud Datalab is a shared resource accessible to all the members of the associated cloud project.
Results saved in the notebook remain in persistent format on the disk.