80% of data is unstructured

So why do most AI/ML tools only handle structured data? Pachyderm’s automated versioning and data-driven pipelines easily scale to petabytes of video, audio, text and genomics data. Unstructured data is anything that doesn’t easily fit into a database or the rows and columns of a spreadsheet. That includes everything from videos for film and television, music and voice audio, large reams of text like a novel, and biotech driven data like genetics.

There are four key categories of unstructured data

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Video / Audio

Pachyderm’s parallel processing engine lets your team tear through huge audio and video datasets 10 to 100X faster than processing them linearly.

Whether you’re working in Media & Entertainment doing automatic subtitle generation, or dynamic ad insertion into online videos, or processing closed circuit video feeds, or track packages and cargo movements, or monitoring industrial machines on factory floors, Pachyderm can help you do it faster and more reliably.

Some good examples of unstructured data are:

  • Streaming videos
  • TV and movies
  • Closed captioned video feeds
  • Call center audio
  • Meeting recordings
  • Weather data

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Imagery

Images challenge most AI/ML platforms because you’re dealing with lots of little files or big binary files. Shoehorning images into databases meant for highly structured data simply doesn’t work well.

Pachyderm lets you rip through big stores of images fast, feeding them to parallelized workers, so you can do everything from finding hidden streets and buildings in satellite imagery, to spotting pedestrians in autonomous vehicle vision systems, to facial recognition for security.

Some good examples of unstructured data are:

  • Satellite imagery
  • Photographs
  • Medical imagery such as CT
  • MRI scans
  • Radiology pictures
  • Microscope images
  • Astronomy images

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Unstructured Text

We’ve known how to deal with structured text for decades, so it’s no surprise that most companies focus on the tried and true database as their backend. But for the tremendous amounts of unstructured text pouring into datacenters, everything from financial reports, to chat logs, to Tweets and Slack posts, databases just don’t work.

Pachyderm’s file system based approach lets you do next-generation NLP, business analytics, legal document analysis and more.

Some good examples of unstructured data are:

  • Novels
  • Wikipedia Pages
  • Tweets
  • Slack
  • Reddit and Discord posts
  • Call center logs
  • Meeting minutes
  • Legal contracts


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Biosciences / Health

Healthcare, biotech and pharmaceutical companies looking to leverage the next generation of machine learning to improve their understanding of genetics look to Pachyderm to unlock hidden insights in the universal code of organic life.

Whether you’re doing advanced drug discovery, risk analysis for trials, repurposing existing drugs, looking for new targets for existing drugs, Pachyderm can help you dramatically speed up your data pipelines and get drugs and cutting edge-therapies to market faster and more successfully.

Some good examples of unstructured data are:

  • Health reports
  • Unstructured text from pathology
  • Radiology and doctor’s note taking
  • Clinical reports
  • DNA data
  • Research
  • Published papers

Case studies

See how Epona Data Science made their model throughput effectively continuous. Every single model they have and every sample, especially genetics samples, runs through the pipeline, gets tested and uploaded to the website in minutes.

You can build these really complex workflows, and in every case Pachyderm serves as this amazing glue to link all of these systems together.


Ryan Smith, Head of Data Science

See case study

See how Agbiome cuts down on manual steps and automatically processes their genetics data with speed and agility.

“Pachyderm helps us convert our existing data science pipelines from manually managed scripts to scalable, repeatable end-to-end workflows; enabling us to focus more on developing transformative technology to drive agriculture forward instead of wrangling infrastructure.”

Mauricio Borgen Director of IT & Scientific Compute

See case study

Data Driven Pipelines

Wrangling unstructured data easily and effectively

Database driven platforms simply don’t provide the right backend to manage the massive amounts of unstructured data your machine learning teams are struggling with right now. To truly unlock the power of your data you need an AI/ML platform that treats unstructured data as a first-class citizen, not an afterthought.


Pachyderm delivers a number of essential features for processing any data with any language:

Work directly with any file type in your code, no schema or complex queries required

Track every version of your code, models and data with automatic versioning and lineage tracking

Supports any tool, framework or language including Python, R, Rust, Java, C++ or BASH

Scales to petabytes of information with highly parallel processing with no extra code, and incremental processing of only new or changed data

Powerful deduplication of data with content-based chunking keeps storage costs low regardless of the number or size of files

Runs on any cloud or on-prem environment using standard object stores like S3, Azure Blob Storage, and Google Cloud Storage

Contact us to learn more about how Pachyderm handles Unstructured Data

Database driven platforms simply don’t provide the right backend to manage the massive amounts of unstructured data your machine learning teams are struggling with right now. To truly unlock the power of your data you need an AI/ML platform that treats unstructured data as a first-class citizen, not an afterthought.

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