5 Data Engineering Projects: The Best One’s to Go For

Data engineering is one of the most important parts of big data. If you want to earn a degree in data engineering and need some sample projects to practice on (or learn from), you’ve come to the right place. In this blog, we’ll talk about data engineering project ideas which you can implement. We will also be discussing data engineering projects for beginners. 

To begin with, let us understand who a data engineer is.

Who is a Data Engineer?

Data engineers take data in its raw form and turn it into information other data experts can use. Data engineers ensure that all an organization’s data sources are the same so that analysts and scientists can use the same data. Data engineers are like people who build aeroplanes, while data scientists and analysts are like people who fly planes. The first one can’t do its job without the second one. Analysts, Big Data Engineers, and other people in the data science community have been talking about data engineering through word of mouth.

Now, without further delay, let us look at the best data engineering projects.

Data Engineering

5 Best Data Engineering Projects

Extract, Transform and Load (ETL)

Extract, Transform, and Load (ETL) include:

  • Taking information from its source.
  • Transforming it for analysis.
  • Loading it into a final database.

All three processes are typically supported by ETL software. 

By making an ETL project, which includes data extraction, processing, analysis, and visualization, you can show that you understand the whole data engineering process. A popular project is to build a data pipeline that can take in sales data in real-time. This data pipeline makes it possible to look at essential sales indicators like:

  • Costs and income for each country
  • Units sold vs units cost per region
  • Revenue versus profit by sales channel and region
  • Sales of a product by region

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Build Data Pipelines

A data pipeline is a system that lets information move from one platform to another. As inputs, the results of one step go into the next. Since a recommendation engine is a mix of product ratings and information about how users act, it is a great project to show that you know how to build data pipelines. 

With Spark SQL and the Movielens dataset, you can use Azure to make a platform for recommending movies. Spark SQL on Azure will be used to analyze the dataset, and based on the results, the data pipeline will be built. 

Sentiment Analysis for Stocks

Stock sentiment affects how volatile the market is, how many trades are made, and how profitable a company is. Data engineers can track how news stories and social media affect stock prices daily by using natural language processing. 

Data Visualization

“Data visualization” refers to how these kinds of pictures are made. If you look at a graph or chart, you can get a clearer and more concise picture of the data than if you read it word for word.

Let’s say you want to know how many people in your area watch Game of Thrones. It would take a long time to ask each person in person. 

You could instead make a map with everyone’s addresses and use different colours to show who watches Game of Thrones and who doesn’t. Just look at the map to see who watches Game of Thrones.

Data Ingestion

“Data ingestion” is the process of getting information from one place to another to be analyzed. Most of the time, people go to the data warehouse, a specialized database made to make reporting easier. 

The ingestion process is the most important part of any analytics framework. This is because analytics systems further down the line needs uniform and easy access data. According to best practices, data collection and cleaning should take up 60–80% of your analytics project.

Streaming and batching are two main ways to get data into a system. There are two ways to get data: in big chunks from sources like databases or a steady stream from sources like sensors. 

Both ways have pros and cons that you should think about before deciding which one to use.

Indeed, we have discussed five top data engineering project ideas. You can learn from the ideas and create a project of your own.


Do you want to get ahead in the field of data engineering?

Do you like to learn important AWS and Azure-aligned data engineering skills?

If that’s the case, connect with the Education Nest right away. Its applied learning program will help you get a job in the field by giving you professional experience and letting you build real-world data solutions that companies worldwide can use.

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