What is DataOps?
Your data is everyplace, and that’s part of the problem. Siloed data becomes an indeed bigger problem when your data and development teams also work in silos, causing a slow response to any incident. This lack of collaboration affects other areas of your business, too, from bug fixing to aim setting, making overall data use and operations inefficient.
In DataOps platform, you can eliminate the distinction between data- and development-focused teams through collaborative work to develop an overview of the data acquisition journey. As a result, incident responses will accelerate, bugs will be fixed faster, and a cohesive team will be able to set and update performance goals in real-time. Your data will be agile, accurate and efficient from end to end.
DataOps was first introduced by Lenny Liebmann on June 19, 2014.
In simple words, “DataOps is a set of practices, processes and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and promote a culture of continuous improvement in the area of data analytics”.
What is the use of DataOps?
- Build Agility into Your Hybrid Cloud – The cloud is a powerful tool, but it serves your workflows, not the other way around. A data team can’t maximize business agility with inefficient workflows. The DataKitchen DataOps Platform delivers on the agile promise of the cloud by aligning the people, processes, and technologies of the data analytics organization across complex hybrid environments and cloud migrations.
- Orchestrate Across a Hybrid Cloud – Seamlessly orchestrate robust multi- and hybrid-cloud analytic production and development pipelines. DataKitchen’s agent-based architecture facilitates the interface between different environments, no matter where the data resides.
- Keep Teams Coordinated – Eliminate silos between teams working across environments. Automated orchestration, testing, and monitoring spans environments to keep the end-to-end process coordinated. Teams can work together while still maintaining their independent environments and toolchains.
- Mitigate Cloud Migration Risk – Run cloud and on-prem tools in parallel, comparing results after each processing step. Use tests to catch discrepancies and address them before users notice. When ready, confidently migrate to new environments one component or pipeline at a time.
List of DataOps Certification
- DataOps Certified Professional (DOCP)
- IBM Data Engineering Fundamentals
DataOps Certification Path
- DevOpsSchool-DataOps Certified Professional (DOCP)
- DevOpsSchool-Dataops Fundamental Training
- IBM-Data Engineering Fundamentals
DataOps Certification Cost
- DevOpsSchool-DataOps Certified Professional (DOCP)- Rs 4999/-
- DevOpsSchool-Dataops Fundamental Training- Rs 4999/-
Best salary for DataOps Certified Professional
- The average salary of Rs 10,98,448 per year in India.
Best DataOps Certification Tutorials