Some good Data Engineering projects are:
Extract, Transform, Load (ETL):
The process of obtaining data from its original source, preparing it for analysis, and putting it into a destination database is known as extract, transform, and load (ETL). Most ETL programs are capable of performing all three phases.
Building an ETL project demonstrates that you understand the entire data engineering process, from data extraction and processing through data analysis and visualization. Building a data pipeline that ingests real-time sales data is a popular undertaking.
Live Twitter Sentiment Analysis with Spark:
People’s opinions are more essential than traditional media when it comes to influencing buying decisions or determining people’s sentiment for a political party. That means there’s a lot of room for marketers on Twitter. Twitter sentiment is a word that refers to the examination of sentiments in tweets submitted by people.
Analyze Security Breach:
The typical technique to countering cyberattacks entails collecting data about viruses, data breaches, phishing efforts, and other attack vectors and analyzing the data to build a digital fingerprint of the attack. To detect potential attacks, these fingerprints are compared to files and network activity.