What Will You Learn?
• List basic skills required for an entry-level data engineering role.• Discuss various stages and concepts in the data engineering lifecycle.
• Describe data engineering technologies such as Relational Databases, NoSQL Data Stores, and Big Data Engines.
• Summarize concepts in data security, governance, and compliance.
About This Course
Provider: coursera.org
Format: Online
Duration: 12 hours to complete [Approx]
Target Audience: Beginner
Learning Objectives: This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores,
and gathering, importing, wrangling, querying, and analyzing data
Course Prerequisites:NA
Assessment and Certification:Earn a Certificate upon completion from the relevant Provider
Instructor: Raj Ahuja
Key Topics: Data Engineering,Ecosystem,RDBMS,NoSQL,ETL
Topic Coverd:
- Introduction to Data Engineering
- Modern Data Ecosystem
- Key Players in the Data Ecosystem
- Skills and Qualities to be a Data Engineer
- Responsibilities and Skillsets of a Data Engineer
- Overview of the Data Engineering Ecosystem
- Types of Data
- Languages for Data Professionals
- Overview of Data Repositories
- RDBMS
- Foundations of Big Data
- Big Data Processing Tools: Hadoop, HDFS, Hive, and Spark
- Architecting the Data Platform
- Factors for Selecting and Designing Data Stores
- How to Gather and Import Data
- Tools for Data Wrangling
- Querying and Analyzing Data
- Performance Tuning and Troubleshooting
- Governance and Compliance
- Career Opportunities in Data Engineering
- Data Engineering Learning Path
- Advice to Aspiring Data Engineers
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