DATA ENGINEERING

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• Introduction to Data Engineering
•  Different Products of Power BI 
•  Python Projects Assignments
•  Power Query - Introduction 
•  Import data into Power Query 
• Assignments 

• Python for Data Engineering
• RDBMS
•  Projects 
• Assignments  

• NOSQL
• Big Data Engineering
• Assignment
• Quiz 

• Internship Project 1 - 2 
• Internship Project 3 - 4
• Report Writing 
• GitHub
• Technical Interview Questions
• Quiz 2
• Assignment
• Quiz 3 

•  Resume Building
•  Technical Mock Interview
•  LinkedIn
•  HR Mock Interview
•  Task Submission 

 Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. 

• Apache Hadoop 
• Relational and non-relational databases
• Apache Spark
• Python
• Julia    

Hadoop is an open-source framework, which is used for data manipulation and data storage, as well as for running applications on units called clusters. Hadoop has been the gold standard of the day when it comes to working with and handling Big Data.

The main advantage is the easy provision of the huge amounts of space needed for data storage and a vast amount of processing power to handle limitless jobs and tasks concurrently.

Data Engineers maintain the data infrastructure to support business applications. As part of their responsibilities, they fuel Artificial Intelligence analytics and the Machine Learning process.

Various positions held by a Data Engineer are listed below:

• Data Architect 
• Data Engineers 
• Database Administrators 

 The data engineer is someone who develops, constructs, tests and maintains architectures, such as databases and large-scale processing systems. The data scientist, on the other hand, is someone who cleans, massages, and organizes (big) data.