Use Cases

Polly for Bioinformaticians

Empowering bioinformaticians with ML-ready data to drive the success of multidisciplinary teams.

The Code-first Data Platform for Accelerated Discovery


Ingest Data from Heterogeneous Sources

Automate data ingestion, transformation & storage using Polly's connectors. Spend your time discovering rather than retrieving and wrangling data.

Get your hands-on analysis-ready data pipelines and cut time to analysis by 70%.

Increase efficiency by utilising ETL processes as reusable code.


Seamless Data Querying

Easily navigate through heterogeneous data, retrieve metadata summaries, and download relevant datasets using powerful querying capabilities on Polly.

Augment your search by writing simple queries at the sample or feature level metadata.

Scale complex queries using Polly Python to create cohorts and integrate datasets from various sources.


Uncomplicated Data Connectivity & Consumption

Polly Python enables unrestricted data connectivity and consumption between OmixAtlas and your preferred platforms.

Stream ML-ready data to various computing platforms while maintaining control over data consumption metrics.

Data is further transformed by file converter functions to make it compatible with big data and web applications.

Key Features

Metadata Harmonization

Datasets on Polly are mapped with harmonized & queryable metadata, streamlining  search for relevant datasets.

Programmatic Interface

Stream ML-ready data to a platform of your choice using API-based integrations via Polly's programmatic interface.

Scalable Infrastructure

Utilise Polly's notebooks, dockers, or machine types to scale computational requirements based on the complexity of your job.

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