DataOps Methodology に戻る
IBM による DataOps Methodology の受講者のレビューおよびフィードバック
コースについて
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.
人気のレビュー
フィルター：
DataOps Methodology ： 1 - 1 / 1 レビュー
by Dean T
•2021年10月22日
Really enjoyed this, explains all the proccesses really well
Coursera Footer
©2021 Coursera Inc.All rights reserved.
