Learn how to automate data life cycle events and governance through Continuous Delivery (CD) pipelines and Self-Service Portals
As enterprises seek to deliver high velocity software releases, it becomes essential that the data lifecycle processes keep pace and that the benefits of DevOps practices extend to data environments. Mphasis Stelligent has now adapted our proven ‘automate everything’ approach for use throughout the data lifecycle. Automation of data events and integration with Continuous Delivery pipelines affords a number of benefits and extracts value from your data:
Faster Cycle Time
Reuse of database and transformation code, continuous integration between applications and data, and faster feedback for development teams all equate to reductions in the data development cycle.
Focus your development efforts on solutions and products that extract value from your data. Faster cycle times allow for experimentation and iteration on data transformations, reporting, and machine learning models.
Improve Data Quality
Test driven development and automated quality controls ensure that the integrity of your data is high from creation, through transformation, and into value extraction.
Scalability and Reliability
Automated infrastructure allows your environment to adapt on-demand to sizing and capacity requirements. Codifying infrastructure improves reliability and allows iteration and continuous improvement of the data systems. Continuous monitoring provides feedback to systems operations teams.
By reducing manual tasks your increase your development capacity and reduce errors in the data lifecycle.
The Mphasis Stelligent DataOps program has proven capabilities to improve the speed and accuracy of analytics, data quality, and value extraction practices and processes. Leveraging automation, data democratization, and greater collaboration among data scientists, engineers, and other technologists, the Mphasis Stelligent DataOps program can help organizations improve the time-to-value of their data.
Full implementation, includes integration with our DevSecOps solutions, providing secure control of data access and content. DataOps CI/CD becomes an extension of your application CI/CD process increasing quality and decreasing the release cycle time for your entire application stack.
The DataOps program is foundational to implementation of higher level Machine Learning (ML) and Artificial Intelligence (AI) environments. Automation at the data operations level ensures timely release of quality data for ingestion by ML and AI models.
For the Corporate Data Office (CDO) and Business Teams
The DataOps framework provides the capability to extract value from data in a timely manner and with high levels of quality. This brings agility to business decisions and gives you a competitive advantage. While others take weeks or months to understand their data, you will have key information available in minutes.
For the Data Operations Team
The DataOps framework means that you can receive a request for a new report or transform in the morning and then develop, test, iterate, and release to production by afternoon. Short feedback cycles mean developers can iterate quickly and experiment without fear of lost time or efforts. Your team can focus on bringing value to data with continuous innovation, development, design, release and test within minutes.
For the Data Architect
Automation or data organizational tasks and data model development with a DataOps framework mean you can focus on design and development. With a data pipeline, you ensure validated data deployments including consistent logical data models and organizational data properties. Publish validated environments, including automated enforcement of data quality rules, for self-service consumption by application teams.
Want to learn more? DataOps Workshops Available
The Stelligent DataOps workshop provides the framework for your data and analytics teams to implement a DataOps practice. For each topic, an assessment is made of the current posture and steps to achieve full DataOps practice are identified. Best practices are reviewed and incorporated into the enablement plan. A high-level project plan is created and we discuss how to accelerate achieving implementation of DataOps framework.
Please contact us to schedule a DataOps Workshop for your data teams.