Free ETL Projects For Your Data Analytics Portfolio

When looking for portfolio projects, some of the best ideas come from finding new trends around you.

The reason is trends are inherently recent, the market is less saturated and it boosts your resume’s worth and makes it unique.

In this blog I will share and deep dive into three free ETL projects.

Extract, Transform, and Load, I don’t think you are unaware of this important term, even if you are a beginner in the field of data. But for those folks who are completely new to the world.

I’ll quickly explain it with a real-world example. So we move to projects.

ETL —

ETL stands for Extract, Transform, and Load. It is a data integration process in the fields of data (i.e. data science, data engineering, data analysis, etc.) that combines data from multiple sources into a single, consistent data store that is loaded into a data warehouse or other target system.

For example, Imagine a big retail company that has multiple stores in different locations in a country. Each store has its own database that tracks sales, inventory, and customer data.

The problem is, that the company wants to create a centralized data warehouse where it can store all of this data in one place so that it can be easily analyzed.

To do this, the company would use an ETL process.

The first step would be to extract the data from each store’s database. This could be done using SQL queries or by exporting the data to a flat-file format. Once the data has been extracted, we move to the next step which is transformation.

Transformation may involve cleaning the data, converting it to a common format, or merging data from different tables. For example, the company may need to merge data from the sales table with data from the customer table to create a unified customer view.

Finally, the transformed data is loaded into the target data warehouse. This is the last step of the ETL process where the data is loaded into the data warehouse.

It can be then used by business analysts to generate reports and dashboards, identify trends, and make better business decisions.

Let’s get into projects😀!

1. NYC Arrest Data: Data Modeling, Analysis, and Visualization

Unlocking the Secrets of NYC Crime. New York City is one of the most vibrant and diverse cities in the world but also faces its fair share of crime challenges.

In this project, we analyzed a dataset of arrests made by the New York State Police Department. We created a dimensional model for the dataset. We used Alteryx and Talend to build ETL pipelines to process, clean the data, and create dimensions and facts in the destination database.

We then used Tableau and Power BI to visualize the necessary database details.

Our analysis revealed a number of key insights, including:

• The most common types of arrests in New York City are drug-related offenses and property crimes.
• Arrests are concentrated in certain neighborhoods, with the highest rates of arrest occurring in low-income communities of color and more issues.

Tech stack: Azure, ETL basics, Alteryx, Tableau, Power BI What you learn: Alteryx, Visualisation, big query, azure

Source Code Link: NYC Arrest Data: Data Modeling, Analysis, and Visualization

3. Reducing MapReduce Time with Talend Open Studio

This project is a step-by-step guide by @edureka an e-learning platform that has created many top courses in almost every field. This project focuses on the big data tool Talend its strength & its industrial importance.

Talend Open Studio is the perfect tool for businesses that want to speed up their big data processing and get insights from their data faster.

Big data is a powerful tool for businesses of all sizes, but it can be challenging to process and analyze large datasets quickly and efficiently. MapReduce is a popular distributed computing framework for processing big data, but it can be complex to use and optimize.

But with Talend Open Studio, you can:

• Use pre-built MapReduce components to perform common tasks, such as sorting, filtering, and joining data.
• Partition your data to improve the performance of your MapReduce jobs.
• Use a distributed file system, such as HDFS, to provide fast access to data from all nodes in the cluster.

This project covers the basics of Talend and you will find it very helpful to your resume especially when you are applying to big corporates.

Tech stack: ETL, big data

what you learn: Mapreduce, ETL, pipeline, Talend studio

Full Step-by-Step Project Here: Reducing MapReduce Time with Talend Open Studio

3. MDB Movie ETL: Building Data Pipeline for Movie Analysis

The silver screen is a magical place where people’s dreams come to life. But there are secrets behind the scenes for a movie to be a successful movie. How do we understand the tastes and preferences of audiences around the world? Let’s find out!

This project aims to answer these secret questions through a data-driven analysis of movies from multiple sources, including IMDB, MoviesLens, The Numbers, and BoxOffice Mojo.com.

We will use Talend to perform ETL processes to extract, transform, and load the data into a staging database. Then, we will use Tableau and Power BI to visualize the data and uncover hidden insights

Tech stack: ETL basics, big data, visualization, SQL What you learn: Talend, Power BI, Tableau, ETL workflow.

Find the Source Code Here: MDB Movie ETL: Building Data Pipeline for Movie Analysis

That’s a Wrap. Enjoy❤

I am Uzman ali, and I talk about data for Tech/non-Tech folks.