In action

Pilosa was initially built to power lighting fast segmentation queries from a large and disparate data set. Along the way we discovered that it is also especially helpful with data science.

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Chemical Similarity and the Tanimoto Algorithm

Bioinformatics

Chemical similarity is essential to pharmaceutical development. Running Tanimoto algorithms over Pilosa clusters allows researchers to conduct exhaustive searches of existing structures to identify target chemicals, accelerating drug development.

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Taming Transportation Data

Smart Cities

Transportation systems are vital to economic networks but produce massive amounts of data that are difficult to analyze. Using New York City taxi data, we harnessed Pilosa's ability to work across datastores while supporting granular attributes.

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Understanding Fans at Umbel

Audience Segmentation

Umbel is where Pilosa’s journey began. See how the Umbel platform uses Pilosa to create highly-specific customer segments, allowing clients to personalize their messaging and increase revenue with data-driven, targeted campaigns.

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Monitoring Network Traffic

Network Security

Modern network attacks require an increasingly complex infrastructure of intrusion prevention, creating datastores which grow exponentially. Layering Pilosa atop existing security solutions allows us to analyze high-volume network data and even predict network intrusions.