IBM - DataOps Methodology
- Offered byCoursera
DataOps Methodology at Coursera Overview
Duration | 10 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
DataOps Methodology at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Beginner Level None
- Approx. 10 hours to complete
- English Subtitles: English
DataOps Methodology at Coursera Course details
- DataOps is defined by Gartner as "a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and consumers across an organization.
- Much like DevOps, DataOps is not a rigid dogma, but a principles-based practice influencing how data can be provided and updated to meet the need of the organizations data consumers.
- The DataOps Methodology is designed to enable an organization to utilize a repeatable process to build and deploy analytics and data pipelines.
- By following data governance and model management practices they can deliver high-quality enterprise data to enable AI. Successful implementation of this methodology allows an organization to know, trust and use data to drive value.
- In the DataOps Methodology course you will learn about best practices for defining a repeatable and business-oriented framework to provide delivery of trusted data.
- This course is part of the Data Engineering Specialization which provides learners with the foundational skills required to be a Data Engineer.
DataOps Methodology at Coursera Curriculum
Establish DataOps - Prepare for operation
Introducing the DataOps Methodology
DataOps Methodology Phases
Course Structure and Learning Objectives
DataOps Case Study
Introduction to AI Ladder and DataOps Capabilities
Data Strategy Overview
Data Strategy Considerations
Data Strategy Case Study
Establish Team Introduction
Team Roles and Responsibility
Team Organizational Structure
Review Questions
Review Questions
Establish DataOps ? Optimize for operation
What is DataOps Toolchain?
DataOps Toolchain in Practice
Establish Baseline Introduction
Models and Operating Standards
Glossary and Catalog
Policies and Rules
Measuring Business Value
Defining Data Task KPIs
Prioritizing a Data Task
Configuring Data Sprints
Review Questions
Review Questions
Review Questions
Iterate DataOps - Know your data
Discover
Classify
Review Questions
Review Questions
Iterate DataOps ? Trust your data
What is Data Quality?
Data Quality Framework
Manage Policies
Case Study
Review Questions
Review Questions
Iterate DataOps ? Use your data
Self Service
Data Movement and Integration Considerations
Data Movement and Integration in Practice
Improve/Complete
Case Study
Review Questions
Review Questions
Review Questions
Improve DataOps
Review and Refine DataOps
Review Questions
Summary & Final Exam
DataOps Methodology Summary
Final Exam
DataOps Methodology at Coursera Admission Process
Important Dates
Other courses offered by Coursera
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