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DataOps Methodology
Master DataOps principles to improve data management, integration, and automation across your organization.
Course Cost
₹ 2,699
Beginner
Skill Level
10 Hours
Self-paced lessons
This course introduces the DataOps methodology, a collaborative data management practice that enhances communication, integration, and automation of data flows. Students will learn to establish a repeatable process for building and deploying analytics and data pipelines, following data governance and model management practices. The curriculum covers the entire DataOps lifecycle, from establishing teams and toolchains to iterating on data discovery, quality, and usage. Learners will gain practical skills in articulating business value, prioritizing data tasks, and implementing data movement and integration projects.
3,480 Enrolled
English
What you'll learn
Understand the fundamentals of DataOps and its role in data management
Establish effective DataOps teams and toolchains
Implement data discovery and classification techniques
Develop strategies for ensuring and improving data quality
Learn data preparation and transformation methods
Understand data movement and integration considerations
Apply DataOps principles to real-world business scenarios
Measure and articulate the business value of data initiatives
Skills you'll gain
This course includes:
2.96 Hours PreRecorded video
14 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 7 modules in this course
This course provides a comprehensive introduction to the DataOps methodology, designed to enable organizations to utilize a repeatable process for building and deploying analytics and data pipelines. Students will learn about the fundamental principles of DataOps, including team structures, toolchains, and the iterative process of knowing, trusting, and using data. The curriculum covers key aspects such as data discovery, classification, quality management, and data preparation. Learners will gain practical skills in establishing DataOps processes, measuring business value, and implementing data movement and integration projects. By the end of the course, students will be equipped to apply DataOps practices to drive value through high-quality, trusted data across their organizations.
Establish DataOps - Prepare for operation
Module 1 · 1 Hours to complete
Establish DataOps – Optimize for operation
Module 2 · 2 Hours to complete
Iterate DataOps - Know your data
Module 3 · 1 Hours to complete
Iterate DataOps – Trust your data
Module 4 · 1 Hours to complete
Iterate DataOps – Use your data
Module 5 · 2 Hours to complete
Improve DataOps
Module 6 · 39 Minutes to complete
Summary & Final Exam
Module 7 · 35 Minutes to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.6
17
Reviews
3,439
Students
1
Course
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.