55 Soda Reviews
Overall Review Sentiment for Soda
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It seems to have everything we needed when looking for a better more experessive validations tool. When we sat down and brainstormed what we wanted we wrote up some thoughts and desires. When we started doing research and found Soda, it was essentially what we had dreamt up. Review collected by and hosted on G2.com.
So far there isn't too much to dislike about Soda. Some of the documentation is a bit hard to follow at times, but after spending a few days with it the team has finally gotten the hang out it. Review collected by and hosted on G2.com.
Soda helps users to do validations without need to write the queries which is the easiest way to play the SQL queries. The integrated platform of soda helps data producers and consumers. It has numbers to data sources available such as Snowflake, BigQuery, Amazon Athena or more. The way it is documented is very easy to understand and helps users to play with the data. Soda is definitely a good Data Quality tool. The best part about the Soda is The Soda Agent which containerised Soda Library that deploys in a Kubernetes cluster in cloud devices provider environment such as Azure of AWS.
Features-
Easy to understand
Highly responsive
Anomaly detection environment
Ease of integration
Data Quality Checks & Scheduled checks
Multiple data source available Review collected by and hosted on G2.com.
There are some limitations about Soda like users need to add additional configuration to the data sources in order to see the preview of the dataset. Soda doesn't performed operations like median and mode. Review collected by and hosted on G2.com.
Soda is a very flexible and customizable tool for quality assertions. We use it to validate the integrity of our data lake. Other tools suchs as dbt tests are good for modeld data but are more limited compared to soda that can be very customizable. Review collected by and hosted on G2.com.
It was a little bit complex in the beggining to integrate with our spark infrastructure but after the first integration was finished the new ones were easier to do. The main issue was due to python libraries conflicts that took some time to solve. Review collected by and hosted on G2.com.
High level markup of DBT tests that would often take me many lines of code to write Review collected by and hosted on G2.com.
Lake of an observability feature on Core. Lack of ability to do impact testing/obtain an impact report Review collected by and hosted on G2.com.
Soda Cloud is a nice and user-friendly interface to both interact with our data and ensure data quality.
The Agreements is a big hit for us! It will take a lot of Jira-work out of the picture, and let us focus on quick-to-implement data quality. Review collected by and hosted on G2.com.
The SodaCL will be a bit of a learning curve for some of our business end-users to start implementing their own data quality. But from the experience we have now, the learning curve is quite managable.
We would also like to see the Agreements be more collaborative. Make it easy for Stakeholders to see what changes have been made when they have to re-approve an Agreement. Review collected by and hosted on G2.com.
The ease of implementing Soda.io was essential for us to promote a data quality culture within our company. We have a wide range of teams and datasets, and before Soda.io, there was no standardized, consistent, and scalable way to implement data quality scans.
Soda allowed us to empower the business units to define and implement their own quality metrics, which boosted our data quality strategy in the company. Furthermore, the solution has been evolving rapidly over the past few years, delivering very useful new features.
The observability power of Soda.io has given us a better understanding of our data quality, and now we can react quickly in case of any incidents.
Another highly positive feature of Soda.io is its API integration capability and its ability to seamlessly integrate with a variety of technologies within the modern data stack, which is essential for our needs. Review collected by and hosted on G2.com.
Despite the ease of implementation of Soda.io by our data engineering teams, less technical teams may still encounter some challenges in creating data quality scans. However, these difficulties have been decreasing with each new feature.
The way datasets and tables are organized in the web interface (Soda Cloud) could be improved. For instance, the creation of groups or namespaces to group datasets and tables within the same context. Review collected by and hosted on G2.com.
Soda.io has been a revelation for our data quality and governance needs. Our organization deals with vast amounts of data, and ensuring its accuracy and consistency is paramount. Soda.io has simplified this process immensely.
One of the standout features of Soda.io is its user-friendly interface. Even team members without extensive technical backgrounds can navigate the platform effortlessly. The ability to set up custom data quality rules and checks has made a significant impact on our data workflows. We can identify and rectify data anomalies and errors quickly, which has improved our decision-making processes. Review collected by and hosted on G2.com.
While Soda.io offers a user-friendly interface for basic operations, some of its more advanced features may have a steeper learning curve. Users with limited technical expertise might find it challenging to take full advantage of the platform's capabilities.
Soda.io's integration capabilities with other software tools and platforms could be further improved. Users who rely on a variety of software applications may encounter challenges in seamlessly connecting and automating data quality processes. Review collected by and hosted on G2.com.
