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Paving the Way to Automated Data Acquisition and Transformation

Leading biopharma organizations are reimagining research, development, and delivery of life-saving therapeutics through automated data acquisition, wrangling, and transformation.

This white paper — Manual No More: Automating the Scientific Data Lifecycle — describes how this world of data science automation has become a reality.

You will learn:

    • The benefits of findable, accessible, interoperable, reusable (FAIR) data in the cloud
    • The importance of multi-point productized integrations
    • The steps to automate the scientific data lifecycle

    Why End-to-end Data Lifecycle Automation Is Critical

    With an automated end-to-end data lifecycle, harmonized scientific data flows freely throughout the biopharma data pipeline to accelerate innovation and support quality. Decoupling instrument control from data publishing enables scaled-up data science automation.

    We discuss these benefits in detail in our white paper:

    • With an automated and remote control interface to interact with instruments, organizations don't need to worry about collecting data with the heterogeneous and fragmented nature of lab data systems.
    • With automated data acquisition across different instruments and lab systems, scientists no longer have to manually locate, transfer, and clean the data.
    • With data pipelines for automated processing and interactive analysis, the data is automatically prepared, analyzed, and presented to the researcher, driving faster decision-making.

    The Tetra Data Platform automates the collection and transformation of data in a format that is compliant, harmonized, liquid, and actionable. See what a modern-day end-to-end data pipeline looks like with TetraScience. Read our entire white paper now.
Spin WangLinkedin

Chief Technology Officer, Tetrascience

Mike Tarselli Linkedin

Chief Science Officer, Tetrascience

Tetrascience Resource
Tetrascience Resource
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