Data Engineering Course

A Data Engineer collects and transforms data to empower businesses to make data-driven decisions. He/She has to pay attention to security and compliance; reliability and fidelity; scalability and efficiency; and flexibility and portability while designing, operationalizing and monitoring data processing systems.

Data Engineering Training Outcomes

The core of Data Engineering involves an understanding of various techniques like data modelling, building data engineering pipelines, and deploying the analytics models. Students will learn how to wrangle data and perform advance analytics to get the most value out of data. As you progress, you'll learn how to design as well as build data pipelines and work with big data of diverse complexity and production databases. You will also learn to extract and gather data from multiple sources, build data processing systems, optimize processes for big data, build data pipelines, and much more. With this course develop skills to use multiple data sources in a scalable way and also master the skills involved in descriptive and inferential statistics, interactive data analysis, regression analysis, forecasting, and hypothesis testing. Also, learn to:

• Comprehend the meaning of Data Engineering
• Understand the Data Engineering Ecosystem and Lifecycle
• Learn to draw data from various files and databases
• Acquire skills and techniques to clean, transform, and enrich your data
• Learn to handle different file formats in both NoSQL and Relational databases
• Learn to deploy a data pipeline and prepare dashboards to view results
• Learn to scale data pipelines in the production environment

What are the prerequisites for this Data Engineering?

To take part in the Data Engineering Training course, the student must have a basic understanding of data structures, algorithms, and programming languages. Knowledge of mathematics, databases, and machine learning is also beneficial. Additionally, the student should have a good understanding of relevant software, tools, and technologies related to data engineering, such as Apache Hadoop, Apache Spark, and Apache Flink.