SERVICES · DATAOPS

DataOps & Governance

Data quality, observability, governance, CI/CD, lineage and operational excellence — continuously. We run your data platform like production software, so the numbers stay trusted long after the migration is finished.
OVERVIEW

The platform is live.
Now keep it trusted.

Most data problems don’t come from building the platform. They come from running it: a schema change upstream breaks a dashboard, a pipeline fails silently, a metric definition drifts between two teams, and nobody notices until a board meeting. XEqualTo brings software engineering discipline — tests, CI/CD, observability, on-call — to your data platform.
The result is a platform that fails loudly and rarely, where every dataset has an owner, every number has lineage, and every change is tested before it reaches a consumer.
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WHERE YOU ARE
WHERE YOU LAND
Pipeline failures found by the business
Changes deployed by hand on a Friday
Nobody knows where a number came from
Quality checked when someone complains
Platform knowledge in one person’s head
OUR CAPABILITIES

Everything it takes to run
a data platform like software.

Data quality & testing

Freshness, volume, schema and business-rule tests on every pipeline run, with data contracts between producers and consumers so upstream changes don’t silently break downstream numbers.

Data observability

Monitoring across pipelines, warehouses and dashboards: lineage-aware alerts that tell you what broke, what it affects, and who owns it — before the business finds out.

CI/CD for data

Version control, automated tests, environments and code review for dbt, Airflow and warehouse changes — so deployments are boring and rollbacks are one click.

Catalog, lineage & governance

Every dataset discoverable, every number traceable back to its source, every rule documented, and ownership assigned — governance the platform enforces, not a policy PDF.

Managed operations

Runbooks, on-call, incident management, cost guardrails and continuous performance tuning — run by our engineers as a managed service, or set up and handed to your team.
OUR APPROACH

Baseline, instrument,
automate, operate.

We start by measuring how reliable the platform actually is, then add the tests, observability and delivery pipeline that turn it into something a team can run calmly — and, if you want, we run it.
01
Weeks 1–2

Baseline

Inventory pipelines, datasets and consumers. Measure failure rates, freshness, incident response and the datasets nobody owns. Map the blast radius of the most common failures so the first fixes go where they matter.
Pipeline inventoryReliability scorecardOwnership gapsIncident history
02
Weeks 2–6

Instrument

Add freshness, volume, schema and business-rule tests, lineage and a catalog. Wire alerts to owners with the affected downstream assets attached, so a failure comes with context instead of a stack trace.
Data testsLineage & catalogObservabilityAlert routing
03
Every change tested

Automate

Put dbt, Airflow and warehouse changes under version control with CI: tests on every pull request, isolated environments, code review and automated deployment. Manual Friday deploys stop.
Version controlCI pipelinesEnvironmentsAutomated deploys
04
Ongoing

Operate

Runbooks, on-call, incident reviews, cost guardrails and continuous tuning — as a managed service from our engineers or handed to yours with the documentation to run it. Either way, nothing lives only in someone’s head.
RunbooksOn-callIncident reviewsManaged service
TECH STACK WE USE

Operated on the platforms
your data already runs on.

Snowflake, Databricks, dbt, Airflow and the major clouds — our engineers run these platforms daily, so the observability and delivery practices fit how they actually behave.
AWS
Databricks
Microsoft Azure
Snowflake
Google Cloud
Power BI
Tableau
dbt
QUESTIONS

Things people ask
before handing over operations.

Not sure whether you need tooling or a team? Talk to us directly — we would rather answer it properly than guess at it.
Contact us
A practice, supported by tools. We bring the engineering discipline — tests, CI/CD, observability, ownership — and use whichever tooling fits your stack, from dbt tests and Airflow to dedicated observability platforms.
Either. Some clients want a managed service with our engineers on-call; others want the practices set up and handed over. Both come with runbooks, tests and documentation.
Ownership per dataset, data contracts, a catalog, lineage, access control, PII handling and retention — specified so the platform enforces them rather than relying on people remembering a policy.
Freshness and schema tests on the critical path typically catch the most common failures within the first month. Structural improvements — CI/CD, contracts, ownership — compound over the following quarter.
Yes. Most engagements start on an existing estate. We instrument what is there first and refactor only where it is the cheapest way to make something reliable.
With a free reliability review: we inventory pipelines and consumers, measure failure rates and freshness, and give you a scorecard and prioritised plan within two weeks.

Ready for a free
reliability review?

We’ll come back with a reliability scorecard for your platform and a prioritised plan to make operations boring. No commitment beyond the conversation.

Contact us
Precision in Every Data Point
Newtown, Kolkata
One office, every time zone
connect@xequalto.com
+91 9147391433
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