Blog Post What is a DataOps Tool: Five Core Capabilities
DataOps tools are part of an emerging technology category that helps organizations streamline data delivery and improve productivity with process integrations and automations.
In December 2022, Gartner® published their first Market Guide for DataOps Tools. Though the DataOps category has existed for years as a methodology, this guide identifies the DataOps Tools market as an emerging class of technology. Tools in this space automate and orchestrate the entire data pipeline — from data collection and ingestion to transformation and delivery.
“Many clients tell us that a DataOps tool is becoming a necessity to reduce the use of custom solutions and manual efforts around data pipeline operations. Buyers seek DataOps tools to streamline their data operations.”
— 2022 Gartner Market Guide for DataOps Tools
What is a DataOps Tool?
The goal of DataOps is to automate and optimize the data management process from end to end. DataOps tools help optimize the cost of data management by minimizing the need for manual intervention.
“By 2025, a data engineering team guided by DataOps practices and tools will be 10 times more productive than teams that do not use DataOps.”
— 2022 Gartner Market Guide for DataOps Tools
For data and analytics (D&A) leaders who want to boost operational excellence and productivity, Gartner recommends using a DataOps tool to combine data management tasks handled by multiple technologies into a comprehensive data pipeline lifecycle. The diagram below shows how DataOps tools support this:
Who is DataOps for?
While the primary buyers of DataOps tools are D&A leaders — such as chief data and analytics officers (CDAOs) — the primary users are data managers and data consumers:
- Data managers include data engineers, operations engineers, database administrators, and data architects
- Data consumers include business analysts, business intelligence developers, data scientists, and business technologists (line-of-business users who are domain experts).
DataOps tools give a unified experience to both data managers and consumers to drive productivity and operational excellence.
“DataOps tools eliminate various inefficiencies and misalignments between data management and consumption users and use cases by streamlining data delivery processes and operationalizing data artifacts (platforms, pipelines, and products).
— 2022 Gartner Market Guide for DataOps Tools”
Here at Stonebranch, we also see interest in DataOps from traditional IT Ops leadership, in addition to D&A leaders. The driver is IT Ops' desire to deliver automation as a service. When IT Ops is involved, it’s typically in partnership with the data teams. In this scenario, IT Ops gains visibility and governance, while data teams are empowered to focus on innovation.
The 5 Core Capabilities of a DataOps Tool, According to Gartner*
DataOps tools offer powerful automation and agility across the full lifecycle of data pipelines. Five key capabilities unite all DataOps platforms:
- Orchestration capabilities include connectivity, scheduling, logging, lineage, troubleshooting, and alerting
- Observability enables monitoring live/historic workflows, insights into workflow performance and cost metrics, as well as impact analysis
- Environment Management features cover infrastructure-as-code (IaC), resource provisioning, and credential management
- Deployment Automation entails version control and approvals
- Test Automation provides validation, script management, and data management
Each of these capabilities is designed to streamline data operations and accelerate success for D&A teams.
Gartner’s Top 3 Recommendations
D&A leaders should keep the following in mind when looking to improve data team performance and remediate operational concerns:
- Evaluate DataOps tools based on key capabilities such as connectivity to your data stack (existing and expected), workflow automation, and release automation.
- Prioritize tools that provide a unified view of workloads across your hybrid IT data stack, while also offering features such as lineage, cataloging, resource provisioning, and environment management.
- Focus on benefits when introducing your selected tool to data managers and consumers. Data managers will be most interested in the ability to monitor workflows and receive proactive alerts; data consumers will appreciate reduced cycle times to access data and improved data integrity.
Putting the Ops in DataOps: Universal Automation Center
Stonebranch Universal Automation Center (UAC) is named as a representative vendor in the 2022 Market Guide for DataOps Tools.
As a DataOps platform, UAC specializes in centralizing control of IT automation processes across enterprise-wide data pipelines. The platform easily integrates with data pipeline-centric tools, including ETL, data lake, data warehouse, and visualization tools.
UAC is ideal for D&A teams who:
- Want to keep using existing data tools but are ready to graduate from open-source schedulers to enterprise-grade platforms.
- Would like a single platform to connect data teams with developers, IT Ops, and CloudOps teams — to help scale their data program.
- Need to operationalize dev/test/prod DataOps lifecycle management methodologies to gain speed and improve data quality.
- Want to gain full visibility across the entire pipeline to optimize uptime with workflow monitoring and proactive alerts
- Have a growing or changing data tool landscape, thus requiring the ability to rapidly build new integrations (or download pre-existing integrations).
- Need to enable data scientists or business technologists with simple self-service capabilities via the platform or third-party tools like ServiceNow, Microsoft Teams, or Slack.
UAC is designed for today’s challenges — and for whatever comes next. To learn more, browse through our customer success stories or reach out to the Stonebranch sales team for a demonstration of the platform.
* "Gartner, Market Guide for DataOps Tools," Robert Thanaraj, Sharat Menon, Ankush Jain, December 5, 2022.
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