Quadrant Knowledge Solutions’ market insights research on Cloud Database Management Systems (CDBMS) platforms provides a detailed insight to users about the significant role of DataOps to manage the controlling of data on the cloud while maintaining the efficiency, speed, and agility of the data pipeline process from collection to delivery
Organizations are increasingly juggling a combination of methods for accessing and ingesting data in the cloud from different sources. By leveraging a DataOps practice to orchestrate and optimize the data streams, the users can operationalize data management and integration to ensure resiliency and agility in the face of constant change.
According to Madhu Kittur, “Users must ensure continuous data flows by automatically identifying and handling data drift and managing them efficiently. DataOps operationalizes data management and integration on the cloud, turning data chaos into a continuous, reliable flow of data to the people and systems that turn it into value. Additionally, DataOps leverages Modern analytics, data science, AI, and machine learning while enabling automation and monitoring across the full data management lifecycle from design to deployment and operations.”
Table of Content:
- Introduction
- Workflow of DataOps
- Use of DataOps in Cloud Data Management
- Role of DataOps in Cloud Data Management
- Reasons to adopt DataOps.
- Limitations of DataOps in Cloud Data Management
- Key Takeaways.
This Market Insight is a part of Quadrant’s Cloud Database Management Studies.
Author: Madhu Kittur, Analyst, Quadrant Knowledge Solutions.
Apoorva Dawalbhakta, Associate Research Director, Quadrant Knowledge Solutions.
