Data engineering is the leading branch of big data. If you want to pursue a data engineering career and wish to present your skills, then you are on the right page. In this blog, we will discuss data engineering project ideas for beginners that you should work on and obtain knowledge of it. As data engineering professionals, being familiar with some topics and technologies before you start working on the projects is essential.
Many companies always look for engineers who develop innovative data engineering projects. Therefore, if you are a beginner, you can start working on real-time data engineering projects. It will not give you valuable insight but strengthen the problem – solving skills and also gain exposure, which is immensely helpful to boost your career. Thus, completing the project and getting the position you want in your career are crucial.
Top Data Engineering Projects that You Must Know
To become a big data engineer, you should be familiar with important and exciting technologies in your field. You will gain knowledge and breakaways by working on data engineering projects.
1. Data Modeling for Streaming Portals
If students want to try their hands on practical data engineering tasks, then data modeling is a great place to start. Streaming platforms like Spotify and Ganna are interested in researching because the media want to improve by taking user suggestions and listening habits. However, engineers must try this data modeling to describe their user data. Python and PostgreSQL are used to build a data integration pipeline.
The word ‘data modeling’ describes creating detailed images showing the connection between numerous data elements. Some the example of user input to consider:
- User’s current favorite saved playlist
- Duration and date stamp during which the user played a song
- Listeners’ favorite albums and songs
- Which music style is preferred by users
2. Building Data Lake
For beginners, this project is fantastic as the requirement of Data Lake is in a growing market. Thus, it allows you to create one and expand the portfolio. In this, organized and
unstructured data of any size are stored in data lakes. It will enable you to add unstructured data first to add data in the storage without structuring it. However, it is one of the best initiatives in data engineering. Also, there is no need to make changes while adding information to Data Lake as the process is simple and allows only real-time data inclusion.
In recent times, Data Lake is needed in technologies like machine learning and analytics. The data engineers can quickly upload various files in the repository using data lakes and perform challenging tasks easily. Thus, you should include a data lake in the project and maximize technological education.
3. Build Data Warehouse
Including a project for building a data warehouse in your data engineering plans is crucial. This project is for those who want to learn more about data warehouses and their use. Data warehouses combine information from multiple sources to make data more useful. Data warehousing, a critical component of Business Intelligence (BI), is crucial for strategic data use. Data warehouses can also be called “Analytic Applications,” “Decision Support Systems,” and “Management Information Systems.”
Business analysts are the primary users of data warehouses. They can store large amounts of data in one place, which is a huge benefit. AWS cloud allows you to create a data warehouse, connect it to an ETL pipeline, and facilitate the movement and transformations of data before storage. You’ll be able to do this task and know everything you need about data warehouses.
4. Implementation of Data Modeling with Cassandra
It is thrilling to see projects such as these that involve data engineering. Apache Cassandra is NoSQL database management software that allows users to access large amounts of information.
It has the advantage of allowing you to use data distributed among many commodity servers, which reduces the risk of data loss. Because your data is distributed across multiple servers, one server failure will only cause your entire business to fail. These are just a few factors that make Cassandra popular with data professionals. It is also highly efficient and saleable.
5. Build and Organize Data Pipelines
If you are a beginner data engineer, start with data engineering projects, one of the best research topics. Our leading task in the project is to streamline the workflow of data pipelines through software. Managing data pipelines is essential for data engineers because it allows them to become experts.
Apache Airflow, a workflow management platform, was launched in 2018 by Airbnb. This software makes it easy to organize complex workflows and manage them easily. You can create workflows in Apache Airflow and manage them. Additionally, plugins and operators are designed for this task. These will allow you to automate your pipelines, reducing your workload and improving efficiency. Automation is a crucial skill in the IT industry. It is used for everything from Data Analytics to Web/ Android Development. Automating project pipelines will give you an advantage when applying to be a project data engineer.
When it comes to the selection of a project, then the best project you choose is a balance between interest and personal interest. Whether you like it or not, personal interest is conveyed through your chosen topic. It is essential to pick the project that you are interested in.
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