Getting data from different sources, cleaning it up, and starting analysis is a messy process. Whether it’s connecting to dozens of databases and disparate systems or unifying it into a single view, every hour you lose to data janitorial work is an hour you’re not finding answers in the data.
data.world makes this process much easier by allowing members to upload data and instantly transform it into a queryable format, automating data ingestion, and giving you a live, collaborative workspace to start analyzing sooner. Whether it’s from a data tool you know and love, a URL, or a file from your drive, our platform can quickly unify your disconnected datasets into something usable and collaborative.
Companies waste money when high-paid professionals spend too many hours finding, cleaning, integrating, and formatting data before the real analysis can begin. Each link in your toolchain adds another level of complexity to this process.
data.world doesn’t replace the tools you love. It makes it easier to get more out of them, without having to create a special data ingest process for every new data project. Plus, data.world integrates into your existing workflows and the tools your teams, clients, and partners use today.
Finding an understanding of your own data shouldn’t feel like searching for needles in a haystack. When your data is enriched with searchable context, you won’t be left wondering why it is the way it is.
data.world is built on a semantic graph database that makes it easier to connect your datasets to each other—and to external sources of data. It’s easy to connect your data from many different sources and automatically update it as often as you want. When your data and context are united on data.world, it's easier to work with and mobilize the right stakeholders for the job.
Connect your data to context, automatically. Ingesting data is as simple as dragging and dropping in a CSV file, or using an integration or API from your data source.
Combine context with your data, all in one place. Know where data came from, what it means, and what to do with it.
Create a virtuous cycle of bringing in your data, analyzing it, and sharing insights—on an ad hoc or sustainable basis.