Anomalo Launches With $33M Series A To Automatically Find Issues In Data Sets
10/28/21, 4:00 PM
Location
Round Type
series a
As companies gather ever-growing sets of data, finding issues with that data that could impact the viability of a machine learning model becomes increasingly important. Anomalo is putting machine learning to work to help solve the data viability issue automatically.
Company Info
Location
palo alto, california, united states
Additional Info
The company has exceeded 7-figures of annualized recurring revenue, tripling its revenue over the last quarter. But every data-driven company quickly encounters one unfortunate fact: much of their data is missing, stale, corrupt or prone to unexpected and unwelcome changes. The round was led by Norwest Venture Partners with Two Sigma Ventures, Foundation Capital, First Round Capital and Village Global participating. “Data is only useful if it’s accurate but data warehouses and BI tools don’t provide any validation so every company struggles with data quality. The company plans to use the money to rapidly grow its engineering and sales teams to keep up with customer demand. Customers on Anomalo BuzzFeed uses Anomalo to catch changes in their most important data sets and metrics. Compared to legacy solutions, Anomalo will help us detect more quality issues with just a fraction of the time invested by our team.” Substack uses Anomalo to empower their small team to keep up with an ever growing collection of data. Mike Cohen, Substack’s Data Manager, said: “With a small data team at Substack, the automated checks that Anomalo provides are like having another data engineer on the team whose primary focus is to ensure data quality and integrity.