Self-service rising, Soda Cloud previews data quality checks

If there’s a term that we can already see listed as a top trend for 2022 by the time the Christmas end-of-year retrospective musings come out, it is self-service.

Not quite the same as technology democratisation i.e. the citizen developer, citizen data scientist, citizen everything technologist trend… self-service in the modern parlance speaks to a more technical audience, yet still champions automated controls that happen without the need to deeper mechanical software engineering involvement.

Surfacing self-service for data quality checking right now is Soda.

Soda co-founder and CEO Maarten Masschelein has blogged to say that there is a change in how organisations operate with data i.e. data teams today are working with a decentralised, domain-driven approach where there is support, accountability and the ability to use and share their data.

At the same time he says, there is a very critical business need for data consumers and business subject matter experts to take ownership of their data quality and be involved in data quality management.

Computationally tied data

Masschelein suggests that data management in modern data architectures is computationally tied into every step of the data flow and product lifecycle.

“[Becuase of this backdrop, we are now] introducing the next milestone in Soda’s mission to bring everyone closer to the data. Available in preview mode, are a new set of features and capabilities that bring Soda Cloud to the next level. The new features and capabilities have been built for the analysts and the data consumers in companies that are building innovative new products using data, as well as the teams responsible for producing data, or managing the contracts with data vendors,” wrote Masschelein.

Within Soda Cloud, [data] analysts can write their own checks and run Soda Scans – which suggests that data analysts are now on their way to be able to fully self-serve and manage their own data quality. 

“To date, many of the existing tools to check data quality have been built for a technical audience, users that can read and write SQL. At Soda, we’re building data reliability tools and an observability platform to help the entire data team discover, prioritise, and resolve data quality issues. We’re simplifying a traditional process and cumbersome approach that has made data analysts heavily reliant on data engineers to implement data checks,” explained Masschelein.

The Soda chief assets that data analysts need to be enabled to fully self-serve, because when they can write their own checks for data quality, the business can really begin to scale with reliable, high-quality data. 

 

 

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