ProjectPro

JUNE 6, 2025

By working on this project, you will gain a comprehensive understanding of crucial aspects like setting up access permissions to ensure data security, establishing triggers for automated data ingestion to keep your data updated, and implementing transformation logic using Cloud Functions.

Data Integration 40

Data Integration Project Data Lake PostgreSQL 40

ProjectPro

JUNE 6, 2025

The ETL (Extract, Transform, Load) process follows four main steps: i) Connect and Collect: Connect to the data source/s and move data to local and crowdsource data storage. ii) Data transformation using computing services such as HDInsight, Hadoop , Spark, etc. Explain the data source in the Azure data factory.

Data Lake 60

Data Lake Metadata SQL Datasets 60

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

MARCH 14, 2023

Data orchestration involves managing the scheduling and execution of data workflows. As for this part, Apache Airflow is a popular open-source platform choice used for data orchestration across the entire data pipeline. A simplified diagram shows the major components of Airbnb’s data infrastructure stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? 5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Singer – An open source tool for moving data from a source to a destination.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Knowledge Hut

SEPTEMBER 29, 2023

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 28, 2024

Role Level: Intermediate Responsibilities Design and develop big data solutions using Azure services like Azure HDInsight, Azure Databricks, and Azure Data Lake Storage. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. This means that Elasticsearch can be easily integrated into different modern data stacks.

Engineering 52

Engineering NoSQL Java Programming Language 52

phData: Data Engineering

JANUARY 3, 2022

phData Cloud Foundation is dedicated to machine learning and data analytics, with prebuilt stacks for a range of analytical tools, including AWS EMR, Airflow, AWS Redshift, AWS DMS, Snowflake, Databricks, Cloudera Hadoop, and more. This helps drive requirements and determines the right validation at the right time for the data.

IT 52

IT AWS Software Engineering Software Engineer 52

ProjectPro

JUNE 6, 2025

Web Server Log Processing In this project, you'll process web server logs using a combination of Hadoop, Flume, Spark, and Hive on Azure. Starting with setting up an Azure Virtual Machine, you'll install necessary big data tools and configure Flume agents for log data ingestion.

Project 64

Project Transportation Data Pipeline Datasets 64