Analytics, DataOps & Automation
DataOps services for SQL Server and SSIS platforms
DataOps brings operational discipline to data platforms: every job monitored, every SLA defined, every change assessed for impact and deployed the same way each time. We put those practices in place for SQL Server, SSIS and Azure environments.
Discuss your environment
SQL AgentSSISAzure
When teams bring us in
Signs you need DataOps support
- Failures are discovered by the business, not the data team
- There are no defined SLAs for when data must be ready
- Changes are deployed manually and sometimes break reports
- Nobody has a single view of platform health
What's included
Our DataOps work
- 01
Monitoring & SLAs
Job, package and pipeline monitoring with freshness SLAs agreed with the business.
- 02
Change impact practice
Lineage-based impact review before schema or pipeline changes are released.
- 03
Deployment standards
Repeatable deployment across environments, with source control as the reference.
- 04
Incident process
Clear routing from failure to owner, increasingly automated.
FAQ
DataOps — common questions
- What's the difference between DataOps and DevOps?
- DevOps focuses on shipping application code; DataOps applies similar discipline to data — pipelines, data quality, freshness and the reports that depend on them.
- Do we need new tools to adopt DataOps?
- Not necessarily. Much can start with SQL Agent, SSISDB history, source control and clear processes. Tools like Dataventra Monitor and Impact make it easier to sustain.
- Where should we start?
- Usually with monitoring and SLAs for the most business-critical loads, then change-impact practice, then automation.
Related Dataventra solutions
Guides
- Guide · 7 min readHow to find everything that depends on a SQL Server table before you change itFind views, procedures, SSIS packages and Power BI datasets that depend on a SQL Server table — with sys.dm_sql_referencing_entities, recursive dependency queries and what they miss.
- Guide · 8 min readMonitoring SQL Agent job and SSIS package failures: a practical guideQuery msdb and SSISDB to find failed SQL Agent jobs and SSIS executions, slow runs, missing rows and stale data — and turn the queries into monitoring.
- Guide · 6 min readAutomatically creating Jira tickets for failed SQL Server Agent jobsDetect SQL Agent and SSIS failures, capture diagnostics and create Jira issues through the REST API — with deduplication, routing and secure credentials.
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Talk to us about DataOps.
Tell us what you're running and what's getting in the way. We'll suggest a sensible first step.