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DataOps Methodology
  • Level Foundation
  • المدة 10 ساعات hours
  • الطبع بواسطة IBM
  • Offered by

عن

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 organization’s 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.

الوحدات

Introduction and Overview

    • 5 Videos
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5 Videos

  • Introducing the DataOps Methodology
  • DataOps Methodology Phases
  • Course Structure and Learning Objectives
  • DataOps Case Study
  • Introduction to AI Ladder and DataOps Capabilities

Establish Data Strategy

    • 3 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

3 Videos

  • Data Strategy Overview
  • Data Strategy Considerations
  • Data Strategy Case Study

Establish Team

    • 3 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

3 Videos

  • Establish Team Introduction
  • Team Roles and Responsibility
  • Team Organizational Structure

Establish Toolchain

    • 2 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

2 Videos

  • What is DataOps Toolchain?
  • DataOps Toolchain in Practice

Establish Baseline

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

4 Videos

  • Establish Baseline Introduction
  • Models and Operating Standards
  • Glossary and Catalog
  • Policies and Rules

Establish Business Priorities

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

4 Videos

  • Measuring Business Value
  • Defining Data Task KPIs
  • Prioritizing a Data Task
  • Configuring Data Sprints

Discover

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Discover

Classify

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Classify

Manage Qualities & Entities

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Review Questions

2 Videos

  • What is Data Quality?
  • Data Quality Framework

1 Readings

  • Case Study

Manage Policies

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Manage Policies

Self Service

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Self Service

Manage Movement & Integration

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Review Questions

2 Videos

  • Data Movement and Integration Considerations
  • Data Movement and Integration in Practice

1 Readings

  • Case Study

Lesson 3 - Improve/Complete

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Improve/Complete

Review and Refine DataOps

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Review Questions

1 Videos

  • Review and Refine DataOps

DataOps Methodology Summary

    • 1 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Final Exam

1 Videos

  • DataOps Methodology Summary

Auto Summary

Discover the transformative power of DataOps with the "DataOps Methodology" course, a key offering in the Data Science & AI domain. Guided by the principles of effective data management, this course focuses on enhancing the communication, integration, and automation of data flows within an organization, akin to the DevOps approach but tailored for data. Offered by Coursera, this foundational course spans approximately 600 minutes, providing comprehensive insights into establishing a repeatable process for building and deploying analytics and data pipelines. Learners will explore best practices in data governance and model management, ensuring high-quality enterprise data that supports AI initiatives. The course is part of the broader Data Engineering Specialization, designed to equip aspiring Data Engineers with essential skills. Ideal for beginners and professionals alike, it emphasizes delivering trusted, valuable data that organizations can rely on. Flexible subscription options are available, including Starter and Professional plans, catering to different learning needs and career goals. Join this course to master the DataOps methodology and drive significant value through reliable data management practices.

Elaine Hanley
Instructor

Elaine Hanley