Comparisons · Data quality testing and monitoring
Decim vs Soda: checks validate data, investigations explain failures
Soda helps teams define and monitor data quality checks. Decim investigates the pipeline, deployment and runtime evidence behind a failed check or unexpected ETL outcome.
Decim and Soda: the short answer
Decim investigates the cause of ETL incidents. Soda is focused on data quality checks, monitoring and the workflows around validating data reliability.
Soda is a natural fit when teams want explicit quality expectations and repeatable checks. Decim is the follow-up surface when a check fails and the team needs to determine what happened in the pipeline.
| Dimension | Decim | Soda |
|---|---|---|
| Primary question | Why did this pipeline produce an incorrect or incomplete result? | Does this dataset satisfy the quality expectations we defined? |
| Starting point | A known ETL incident or failed data expectation. | A data quality check, monitor or contract that needs evaluation. |
| Core artifact | An evidence-backed diagnosis and human-reviewed solution path. | Quality checks, results, monitors and data reliability signals. |
| Current Decim evidence | GitHub plus scoped Windows directory, file and Event Log tasks. | Soda's configured checks and connected data-quality context. |
| Best use together | Investigate the cause after a quality check identifies a problem. | Define and detect the quality condition that should trigger review. |
Choose Soda for explicit data quality expectations
A check is valuable because it makes an implicit expectation executable.
Soda fits teams that want to express expectations about their data and run those checks consistently. A quality rule can turn an assumption about freshness, completeness, validity or distribution into a visible result that the team can monitor over time. That is an important control point in a data pipeline. Decim does not replace the quality rule or pretend that a diagnosis can substitute for a clear expectation. When a check is the thing that tells the team a result is wrong, Soda can own that detection and provide the initial failure context.
Choose Decim after the check has failed
A failed assertion narrows the question, but it does not always answer it.
The same quality failure can have very different causes. Missing rows may result from a source selection change, a filter added in the wrong revision, a retry that duplicated a boundary, or a host process that stopped after a partial write. Decim is designed to investigate those alternatives using evidence from GitHub, deployed files and scoped Windows Event Log tasks. The current admin is deliberately focused: it does not currently run database query collectors or ingest third-party quality platforms. Its value is in organizing the evidence for a known incident and making the diagnosis inspectable rather than leaving the failed check as the end of the story.
Turn quality failures into repeatable incident learning
Use the check to detect the pattern and the investigation to understand the condition that created it.
A practical workflow starts with a Soda check result that identifies the asset, expectation and time window. The response team can then use Decim to examine the corresponding ETL run, compare the deployed revision with the repository and collect narrowly scoped host evidence. The final diagnosis can explain whether the check caught a data issue, a pipeline issue or a configuration issue, which keeps future remediation specific. The products can therefore reinforce one another: Soda keeps expectations visible and repeatable, while Decim provides the causal record for incidents that require engineering action. The integration boundary should stay clear in the page copy: Decim supports GitHub and its Windows agent today, and broader quality-platform connectors remain planned.
Common questions
Is Decim a replacement for Soda?
Can Soda tell me why a check failed?
Does Decim run SQL quality checks?
Which tool should own data contracts?
Can the same team use Soda and Decim?
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Compare from a real incident
Bring an ETL incident and the tools you already use. We will separate detection, evidence collection and diagnosis, then show where Soda and Decim each fit.