ProjectPro

JUNE 6, 2025

Develop application programming interfaces (APIs) for data retrieval. Collaborate with leadership and senior management to develop and implement a data strategy to help the organization reach its goals and objectives. Gain expertise in big data tools and frameworks with exciting big data projects for students.

Data Architect 40

Data Architect Data Mining Programming Language Java 40

ProjectPro

JUNE 6, 2025

Top Apache Airflow Project Ideas for Practice A Music Streaming Platform Data Modelling DAG A Data Lake Pipeline DAG A Weather App DAG Using Apache’s Rest API Start Building Your Data Pipelines With Apache Airflow FAQs About Apache Airflow What is Apache Airflow? Is Airflow an ETL Tool?

Data Pipeline 45

Data Pipeline Building Data Lake Raw Data 45

ProjectPro

JUNE 6, 2025

Furthermore, you will find a few sections on data engineer interview questions commonly asked in various companies leveraging the power of big data and data engineering. Data engineers use the organizational data blueprint to collect, maintain and prepare the required data. Briefly define COSHH.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Name a few data warehouse solutions currently being used in the industry. The popular data warehouse solutions are listed below: Amazon RedShift Google BigQuery Snowflake Microsoft Azure Apache Hadoop Teradata Oracle Exadata What is the difference between OLTP and OLAP? Are you a beginner looking for Hadoop projects?

Data Warehouse 40

Data Warehouse Data Mining Recruitment Database 40

ProjectPro

JUNE 6, 2025

Data Engineering Project You Must Explore Once you have completed this fundamental course, you must try working on the Hadoop Project to Perform Hive Analytics using SQL and Scala to help you brush up your skills. AWS, Azure, Google Cloud), machine learning algorithms/models, big data technologies (e.g., SQL, NoSQL).

Data Engineer 45

Data Engineer Data Engineering Cloud Engineering 45

ProjectPro

JUNE 6, 2025

Build an Azure Recommendation Engine on Movielens Dataset Covid-19 Data Analysis using AWS Athena Analyze Yelp Dataset with Spark & Parquet Format on Azure Databricks Apache Spark , Hadoop , Hive , etc. As a data engineer, you must know how to build a data pipeline from raw data using various ETL tools, etc.

Data Engineer 40

Data Engineer Data Engineering Recruitment Engineering 40

ProjectPro

JUNE 6, 2025

With an increasing amount of big data, there is a need for a service like ADF that can orchestrate and operationalize processes to refine the enormous stores of raw business data into actionable business insights. What sets Azure Data Factory apart from conventional ETL tools?

Data Lake 60

Data Lake Metadata SQL Datasets 60

ProjectPro

JUNE 6, 2025

Upskill yourself in Big Data tools and frameworks by practicing exciting Spark Projects with Source Code! Dataflow also optimizes potentially costly procedures like data aggregations automatically. 2) Is Google Dataflow an ETL Tool? Write your project's name, then click CREATE.

Google Cloud 40

Google Cloud Java Big Data Data Ingestion 40

ProjectPro

JUNE 6, 2025

Best Resources to Learn Azure Synapse Analytics The following resources will help you on your path to understanding Azure Synapse Analytics: Hands-On Azure Synapse Analytics Project Ideas for Practice There’s no better way to learn about any big data tool or service than by working on a practical project leveraging it.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

AWS Glue You can easily extract and load your data for analytics using the fully managed extract, transform, and load (ETL) service AWS Glue. To organize your data pipelines and workflows, build data lakes or data warehouses, and enable output streams, AWS Glue uses other big data tools and AWS services.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Conditional Formatting - Data Analysts can highlight cells in a particular color in Excel based on the value of the cell and the criteria they establish. It's an excellent method for graphically highlighting information or finding trends and outliers in data. Furthermore, it certainly works with both versions of the Hadoop environment.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

SEPTEMBER 26, 2021

Basic knowledge of ML technologies and algorithms will enable you to collaborate with the engineering teams and the Data Scientists. It will also assist you in building more effective data pipelines. It then loads the transformed data in the database or other BI platforms for use. Hadoop, for instance, is open-source software.

Big Data 52

Big Data Data Engineer Data Engineering Engineering 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

Knowledge Hut

NOVEMBER 17, 2023

You must be able to create ETL pipelines using tools like Azure Data Factory and write custom code to extract and transform data if you want to succeed as an Azure Data Engineer. Master data integration techniques, ETL processes, and data pipeline orchestration using tools like Azure Data Factory.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

Programming languages like Python, Java, or Scala require a solid understanding of data engineers. Data is transferred into a central hub, such as a data warehouse, using ETL (extract, transform, and load) processes. Learn about well-known ETL tools such as Xplenty, Stitch, Alooma, etc.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

ProjectPro

JUNE 6, 2025

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data.

Data Engineer 49

Data Engineer Data Engineering Engineering Certification 49

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. Briefly define COSHH.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

DECEMBER 7, 2021

AWS Glue You can easily extract and load your data for analytics using the fully managed extract, transform, and load (ETL) service AWS Glue. To organize your data pipelines and workflows, build data lakes or data warehouses, and enable output streams, AWS Glue uses other big data tools and AWS services.

Data Pipeline 52

Data Pipeline Architecture Kafka Data Lake 52

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data.

Data Engineer 52

Data Engineer Data Engineering Engineering Certification 52

ProjectPro

JUNE 6, 2025

Whether you are looking to migrate your data to GCP, automate data integration, or build a scalable data pipeline, GCP's ETL tools can help you achieve your data integration goals. GCP offers tools for data preparation, pipeline monitoring and creation, and workflow orchestration.

ETL Tools 40

ETL Tools Big Data Google Cloud Project 40