We focus on aggregated data, in which each data point reflects multiple people or units, for several reasons.

It is more valuable.

Often, individual data is primarily used to compute statistics like averages and counts. We simplify that process by calculating these things for you. As a result, every one of our millions of data points is meaningful, because it represents the experience of many individual people--not whether one person went to the hospital, but whether many people in the community are going to the hospital for the same reason.

It is cleaner.

Individual data suffers from poor data quality in all but the most rigorous data systems. Sometimes individuals don't answer the question, or a topic doesn't apply to them, or the measurement is invalid. By focusing on aggregates, we guarantee that every single data point is relevant and meaningful.

It is easier to compare data across topics.

Matching up individual data sets is extremely complex and difficult. Additionally, many of our datasets come from healthcare or other sensitive industries, and cannot be matched to other datasets because individual information has been stripped out. Other platforms solve this problem by presenting each topic in isolation, but we believe it's very valuable to look at multiple points of information about the same community.

Our curated data

Our Curated Data