A checklist by TDWI
Modernizing Your DataOps Pipeline to Address Fresh Challenges: 6 Best Practices
To keep pace with fast-changing business requirements, enterprises require a modern set of platforms, tools, skills, and techniques for operationalizing data and analytics. Modern data engineering processes—also known as DataOps pipelines—continuously integrate, transform, and prepare data for production deployment.
Learn how you can eliminate DataOps bottlenecks, migrate pipelines to modern cloud infrastructures, enable centralized visibility, and optimize processes for both low-latency and batch processing. Discover 6 proven best practices for modernizing your DataOps pipelines:
- Define a strong business justification for DataOps modernization
- Identify priority use cases for a modernized DataOps pipeline
- Align DataOps modernization with strategic cloud data platform implementation
- Make the necessary investments in enabling infrastructure, tools, and skills for DataOps modernization
- Bring simplicity into the modernization of the DataOps pipeline
- Restructure the DataOps pipeline in the process of modernizing it
To learn more, download this exclusive checklist by TDWI.
Meet Gathr.
The only all-in-one data pipeline platform
- One platform to do it all - ETL, ELT, ingestion, CDC, ML
- Self Service, zero-code, drag and drop interface
- Built-in DataOps, MLOps, and DevOps tools
- Cloud-agnostic and interoperable
Data
Ingestion-
Change Data
Capture -
ETL/ELT Data
Integration -
Streaming
Analytics -
Data
Preparation -
Machine
Learning
