Knoema has built proprietary data software and methodology to integrate more than 3.2B time series published by more than 1.2k sources.

Our data engineering team has more experience with time-series data integration than any other organization in the world.
On this page, we go deep and discuss the Data Management Tool we built to aggregate and validate data, the challenges this tool helps address, and how we curate data types and sources to provide value to Knoema users.
The Knoema Data Management Tool
Knoema’s proprietary Data Management Tool was built by our team of data engineers to specifically address challenges associated with time series data integration. Our deep expertise is evidenced throughout the tool, from how we capture revisions and reporting methodology changes to how we chain together data integration to visualization, analytic tools, and user customization.

An example of the challenges our tool solves
Knoema’s data management tool is unparalleled when it comes to combining the specific and dedicated everyday tasks of statisticians at organizations like the IMF, EC, ECB, OECD, and the AfDB. This tool, coupled with Knoema’s ability to enable data visualization and dissemination, is Knoema’s strategic competitive advantage in the end-to-end data management market.
Some tools provide powerful statistical methods libraries, some CMS systems excel in data dissemination, and still others streamline processes automation. No other company responds to the unique, complex requirements of the most demanding of clientele – the world’s multilateral statistical agencies. Only Knoema can download bulk data from the DMT into a user-friendly, integrated data environment for data query and report construction as well as export data to multiple standard formats (Excel, CSV, R, SDMX, C#…).
Knoema makes datasets that are notoriously hard to work with easy to digest
There is often confusion that Knoema simply has a lot of public data. We don’t just assemble data in one location; we have data that is both easy and hard to find, and in some cases data that might be “public” but is not readily accessible, or accessible in a format that’s actually useable. This is a problem that we work tirelessly to solve at scale. For many difficult to work with datasets, our team has even designed the dissemination infrastructure for the country or agency that publishes it, ensuring the data is available for Knoema customers.

Data source by type
Knoema doesn’t just archive and organize data, we make it discoverable
At Knoema, we don’t just want to have the world’s largest repository of data, we want to solve challenges related to finding and using it, so that our users can save time getting to exactly what they need. As such, we organize our data geographically in our data atlas, and also by industry, categories, and sources. To see how this coverage looks over the globe, we have a searchable Data Coverage Matrix that helps showcase the breadth and depth of our data coverage by location and category.
Above all, we focus on ensuring the data we have is useful to our users
In addition to volume, we’re also passionate about ensuring that we have datasets that are universally useful, with great resources to answer the most searched queries by data scientists and analysts across the web. We showcase these popular data sets in our Data Coverage Highlights page to easily show users what’s popular with the Knoema data community at large.
