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DataOps
Build scalable data pipelines for delivering trusted, high-quality insights.
Deliver trusted insights faster. Every time.
Data is essential to your success, but traditional data management approaches are often slow, labor-intensive and error-prone. That makes getting data where you need it when you need it a challenge. With DataOps, you can automate your end-to-end data workflows and let SAS take care of the heavy lifting – so you can focus on getting results.
Why DataOps?
Poor-quality data in analytics and AI initiatives can lead to misinformed business decisions. And most organizations say that ensuring data quality and reliability is a major challenge. DataOps can change that with streamlined processes that move data along the pipeline faster, continuously delivering actionable insights and demonstrable business value.
63%
Data consumers who agree that data is outdated by the time it is consumed or analyzed by the organization.1
80%
Expected reduction in data and analytics errors as a result of implementing DataOps.2
60%
Organizations that will have started implementing DataOps by 2023.3
1 DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain, 451 Research, August 2021
2 IDC Futurescape 2021, IDC #US469204203
3 IDC Futurescape 2021, IDC #US46920420
How DataOps Benefits CDOs
Build a true data-driven organization
Expand the adoption of data and analytics to everyone. Build confidence in your use of analytics and data management programs.
Ensure data privacy & protection
Have a strong governance program that applies comprehensive policies to data usage across the enterprise ensuring regulatory and personal privacy compliance.
Integrate data across multiple silos
Gain a unified 360-degree view of data across the organization by streamlining the data integration process and encouraging collaboration among business and tech teams.
Measure your success
Measure the effectiveness of your data initiatives. Monitor your ROI from data and analytics investments with KPIs related to data sharing, data quality, data monetization and customer experience.
How DataOps Benefits Data Engineers
Spend less time finding & fixing data
Manage all new, existing and repeated data requests. Quickly access new, upcoming and complex data that data consumers will need, regardless of location.
Automate processes related to data prep & pipeline
Find ways to automate the data provisioning process.
Shorten cycle time for new analytic requests
Streamline end-to-end processes, from data to insight, and encourage collaboration among business and tech teams.
Reuse data analytics components
Adopt tools and processes for reusing existing code within the data workflow. Boost your data pipeline coding velocity.
How SAS Enables DataOps
Unlock a high level of productivity
Enable multidisciplinary teams to share analytic assets & promote frictionless collaboration in a secure and controlled environment.
Reduce end-to-end cycle time
Orchestrate complex data pipelines across the analytics value chain to accelerate time to insight.
Centralize information governance
Uncover data best-suited for your business needs through an out-of-the-box data catalog.
Democratize data access
Reduce data silos by providing self-service data access to citizen data analysts and business users.
Integrate platform observability
Bring real-time visibility on complex data workloads to reduce analytic errors and increase production efficiency of data operations.
Build trust through automation
Ensure 24x7 data quality control to eliminate day-to-day manual pipeline monitoring through testing automation.
Continuous delivery & version control
Enable continuous analytic deployment and centralized version control through open-source integrations with GIT, Jenkins & Airflow.
Reduce data engineer burnout
Achieve peak productivity and respond quickly to new analytic requests by identifying and eliminating data bottlenecks.
Identify, govern & protect personal data
Evaluate the fitness of data while ensuring governance and monitoring of confidential data with an information privacy assessment.
Explore More on DataOps and Beyond
Want to learn more about DataOps?
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