ProjectPro

JUNE 6, 2025

So, whether you are a seasoned data engineer or just starting your data journey, this exploration of data integration promises to turn your data mountains into golden opportunities. Table of Contents What Are Data Integration Projects? You will use Python libraries for data processing and transformation.

Data Integration 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

The Rossmann Stores dataset is one of the most popular datasets used by Data Science beginners. You can use the dataset and the linear regression machine-learning algorithm to forecast retail sales in this project. You will train and test the data model using the cross-validation method.

Machine Learning 49

Machine Learning Engineering Algorithm Programming Language 49

ProjectPro

JUNE 6, 2025

Experts predict that by 2025, the global big data and data engineering market will reach $125.89 With the right tools, mindset, and hands-on experience, you can become a key player in transforming how organizations use data to drive innovation and decision-making.

Data Engineer 40

Data Engineer Data Engineering Engineering ETL Tools 40

Data Engineering Weekly

MARCH 30, 2025

Save Your Spot → Editor’s Note: Data Council 2025, Apr 22-24, Oakland, CA Data Council has always been one of my favorite events to connect with and learn from the data engineering community. Data Council 2025 is set for April 22-24 in Oakland, CA. link] BVP: Roadmap: Data 3.0

Data Engineer 57

Data Engineer Data Engineering Engineering Pipeline-centric 57

ProjectPro

JUNE 6, 2025

By practicing Kubernetes projects, data scientists can learn how to effectively deploy and scale data processing and analytics applications. Kubernetes enables horizontal scaling, efficiently utilizing computing resources and handling increased data volumes.

Data Science 40

Data Science Project Pipeline-centric Healthcare 40

ProjectPro

JUNE 6, 2025

This makes Python a natural fit for ETL workflows across both fast-moving startups and large-scale enterprise data teams. Here’s why building ETL pipelines with Python is a no-brainer - Python makes it easy to write and maintain complex ETL data workflows. This is where the CSV summary comes in.

Python 40

Python Building PostgreSQL Raw Data 40

ProjectPro

JUNE 6, 2025

Azure Databricks embodies this philosophy by providing a user-friendly interface that simplifies data engineering complexities, helping professionals extract meaningful insights and drive business value. According to a report by IDC, worldwide data generation is projected to reach a staggering 175 zettabytes by 2025.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

Furthermore, the job market is expected to significantly transform, with an estimated 97 million people expected to work in AI-related roles by 2025. About 48% of companies now leverage AI to effectively manage and analyze large datasets, underscoring the technology's critical role in modern data utilization strategies.

Data Analytics 40

Data Analytics Healthcare Machine Learning Data Analysis 40

Data Engineering Weekly

DECEMBER 16, 2024

Evolution of Data Lake Technologies The data lake ecosystem has matured significantly in 2024, particularly in table formats and storage technologies. Data Mesh, Data Products, and Data Contracts Miro exemplifies the shift toward metadata-driven workflows by transitioning from Airflow code to DataHub YAML specifications.

Data Engineer 62

Data Engineer Data Engineering Engineering Unstructured Data 62

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. If we look at history, the data that was generated earlier was primarily structured and small in its outlook.

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

ProjectPro

JUNE 6, 2025

ProjectPro has listed some sample real-time Azure project ideas that will boost the value of your resume in 2025. It uses time-series data and automatically selects the most relevant anomaly detection algorithm for detecting dips, deviations, and spikes from inliers. Anomaly Detector has two types of APIs: univariate and multivariate.

Project 64

Project Transportation Data Pipeline Data Ingestion 64

Ascend.io

MARCH 19, 2025

Data engineering in 2025 isn’t just about moving datait’s about ensuring reliability, security, and scalability as data ecosystems grow in complexity. As pipelines grow more complex and AI-integrated workflows become the standard, the difference between success and chaos lies in the practices data teams adopt.

Data Engineer 52

Data Engineer Data Engineering Engineering Metadata 52

ProjectPro

JUNE 6, 2025

In the big data industry, Hadoop has emerged as a popular framework for processing and analyzing large datasets, with its ability to handle massive amounts of structured and unstructured data. This makes the data ready for visualization that answers our analysis. Analysis large datasets easily and efficiently.

Hadoop 40

Hadoop Project Big Data Media 40

ProjectPro

JUNE 6, 2025

By using the production line dataset by Bosch , you can analyze data to predict internal failures by making use of data that contains information on tests and measurements obtained for each component. Topic modelling can also be used to classify large datasets of emails. to analyze the data. value_counts().plot(kind='bar',

Data Analytics 40

Data Analytics Project Insurance Datasets 40

Data Engineering Weekly

DECEMBER 18, 2024

DEW published The State of Data Engineering in 2024: Key Insights and Trends , highlighting the key advancements in the data space in 2024. We witnessed the explosive growth of Generative AI, the maturing of data governance practices, and a renewed focus on efficiency and real-time processing. But what does 2025 hold?

Data Engineer 113

Data Engineer Data Engineering Engineering Data Lake 113