Data Quality Monitoring and Data Preparation software

Updated: June 22, 2022

2022. Validio, a data quality platform emerges from stealth with $15M

Validio, a startup building tools to improve and ensure data quality — specifically with tools that let users clean up data both stored in data warehouses and elsewhere, as well as in real time, has raised $15 million. Validio is building for data engineers. It’s very technical. But it's focusing on a smooth user experience. That includes using machine learning and statistical analysis to “teach” a users’ system to find and respond more quickly to the data coming through the pipeline; sets of rules that are created automatically for an engineer to use or to complement with customized rules; automated thresholds and auto-resolution capabilities, and more.

2021. Iteratively raises $5.4M to help companies build data pipelines they can trust

As companies gather more data, ensuring that they can trust the quality of that data is becoming increasingly important. An analytics pipeline is only as good as the data it collects, after all, and messy data — or outright bugs — can easily lead to issues further down the line. Startup Iteratively, that wants to help businesses build data pipelines they can trust, has raised $5.4 million seed funding. Iteratively focuses on event streaming data for product and marketing analytics — the kind of data that typically flows into a Mixpanel, Amplitude or Segment. Iteratively itself sits at the origin of the data, say an app, and then validates the data and routes it to whatever third-party solution a company may use.

2020. Avo raises $3M for its analytics governance platform

Avo, a startup that helps businesses better manage their data quality across teams, has raised a $3 million seed round. Avo gives developers, data scientists and product managers a shared workspace to develop and optimize their data pipelines. Good product analytics is the product of collaboration between these cross-functional groups of stakeholders, and the goal of Avo is to give these groups a platform for their analytics planning and governance — and to set company-wide standards for how they create their analytics events.

2020. Truthset raises $4.75M to help marketers score their data

Marketing data quality startup Truthset has raised $4.75 million in seed funding. The company scores the consumer data that marketers are buying on accuracy, on a scale between 0.00 and 1.00. To create these scores, Truth{set} checks the data against independent data sources, as well as first-party data and panels. The platform can even “suppress” consumer IDs that don’t meet a marketer’s standards, so that they’re not used in targeting. And it's compatible with demand-side platforms, data management platforms and customer platforms. It also integrates with the leading data providers, including Facebook, LiveRamp and The Trade Desk.

2020. Toro snags $4M seed investment to monitor data quality

Data Quality Monitoring provider Toro announced a $4 million seed round. Company co-founder and CEO Kyle Kirwan says the startup wanted to bring to data the kind of automated monitoring we have in applications performance monitoring products. Instead of getting an alert when the application is performing poorly, you would get an alert that there is an issue with the data. The monitoring platform helps data teams find problems in their data content before that gets into dashboards and machine learning models and other places where problems in the data could cause a lot of damage

2020. Delman raises $1.6 million to help companies clean up data

Delman, a Jakarta-based data management startup, has raised $1.6 million in seed funding. Originally launched as an end-to-end big data analytics provider, Delman shifted its focus to data preparation and management. Many companies said they had budgeted for expensive data analytics solution, but then realized their data was not ready for analysis because it was spread across multiple formats. Delman’s mission is to make it easier for data engineers and scientists to do their jobs by cleaning up and preparing data.