Language: English
Created by: Prince Patni
Rate: 3.7 / 73 ratings
Enroll: 14,753 students
What you’ll learn
- Concept of Datamesh as a Data Architecture concept
- Steps to implement Datamesh in organizations
- Concept of related terms like Data Fabric, Data Lake, Data Warehouse, Data Lakehouse etc
- Datamesh applications case studies of organizations like Netflix, Paypal etc
Requirements
- No prior experience needed, we will everything about Datamesh from scratch
Description
Every year more data is produced globally. This holds also for companies: more details than ever are recorded from customers, partners, transactions, products and supply chain resulting in more data. According to IDC , “the global datasphere will grow from 45 zettabytes in 2019 to 175 by 2025”. This data forms the raw material from which organizations are drawing valuable, actionable insights. But the collection, integration and governance of this data is still one of the main challenges.
These organizations are now looking at a relatively new concept called “Data Mesh” to overcome these main challenges and inhibitors. Data Mesh is an emerging hot topic for enterprise software that puts focus on new ways of thinking about data. Data Mesh aims to improve business outcomes of data-centric solutions, as well as to drive adoption of modern data architectures.
Top Reasons why you should choose this Course :
- This course is designed keeping in mind the students from all backgrounds – hence we cover everything from basics, and gradually progress towards elaborate topics.
- This course can be completed over a Weekend.
- Wonderful collection of useful resources are shared, that will be updated frequently.
- All Doubts will be answered.
A Verifiable Certificate of Completion is presented to all students who undertake this Data Mesh Fundamentals course.
Who this course is for:
- IT Professionals looking to learn the trending new concept of Data Mesh
- Students and Professionals in Data Domain – Data Scientists, BI Professionals, Database Administrators etc.
- Organizations looking to scale their Data Management techniques
