Datalore
Collaborative data science platform for teams
How Data Teams Use Datalore – 2 New Stories
While the Datalore team is getting ready for the major 2022.3 release, we’d like to share two recently published stories from Datalore customers, Chainalysis and The Center for New Data.
We hope these case studies inspire you to switch your team to Datalore Enterprise – it’s free for teams of up to four people! Maybe you will find challenges you can relate to and see possible solutions implemented by Datalore customers.
How teams at Chainalysis use Datalore
Chainalysis uses Datalore for blockchain analytics, a rapidly expanding field where there is always new data to be acquired and analyzed. They have a lot of data acquisition and processing functions, and they expect them to keep growing.
After adopting Datalore, teams at Chainalysis managed to:
- Reduce the friction of user onboarding.
- Create a top-level interface over a variety of SQL databases, S3, and other data storages.
- Easily share analysis results as recomputable reports.
“Datalore provides us with a top-level interface over all that data, one where data scientists can poke around each of these different data sources and combine them to derive insights.”
– Surya Rastogi, Senior Staff Data Scientist, Chainalysis
How teams at The Center for New Data use Datalore
The Center for New Data processes 300 GB of data daily to measure voting access in the United States. Ensuring high data quality is critical for their research.
Their data quality team uses Datalore to:
- Debug Airflow Pipeline results.
- Build quick visualizations.
- Share reports across the whole organization.
“Datalore allows our team to rapidly prototype and share results with anyone on the team. It’s become a game-changing tool for collaboration across our organization.”
– Chad Rosenberg, Head of Technology, The Center for New Data
Do you have any challenges or hesitations with adopting Datalore? Share them with us in a small meeting! Book a slot to chat with our product team via our Calendly.
Kind regards,
The Datalore team