The Data Engineering hub  is focused on bringing together information, experts, organizations, policy makers, and the public to LEARN more about a topic, DISCUSS relevant issues, and COLLABORATE on enhancing research-driven DE knowledge and addressing DE challenges ….  …. where onAir members control where and how their content and conversations are shared free from paywalls, algorithmic feeds, or intrusive ads.

The onAir Knowledge Network is a human-curated, AI-assisted network of hub websites where people share and evolve knowledge on topics of their interest. 

This About the Data Engineering onAir 2 minute video is a good summary of DE hub mission and user experience. 

If you or your organization would like to curate a post within this hub (e.g. a profile post on your organization), contact matthew.kovacev@onair.cc.

To become an onAir member  of this hub, fill in this short form. It’s free!

Source: Other

Data engineering processes involve the design, construction, and maintenance of systems that handle the lifecycle of data, from its collection and storage to its transformation and delivery for analysis and decision-making.

These processes are crucial for ensuring data is accessible, reliable, and usable by other teams within an organization, like data scientists and analysts.

In essence, data engineering processes are the foundation for leveraging data within an organization. By building robust and efficient data systems, data engineers enable other teams to derive valuable insights and make data-driven decisions.

Source: Gemini AI Overview

Data engineering encompasses a wide range of use cases, broadly categorized by the need to collect, process, and prepare data for various applications. Key areas include real-time analytics, customer relationship management, fraud detection, and supporting machine learning models.

Data engineering also plays a crucial role in areas like financial services, manufacturing, and healthcare, optimizing operations, improving decision-making, and enabling real-time monitoring.

The field is constantly evolving, with new applications emerging as data volumes and complexity continue to grow.

Source: Gemini AI Overview

Data engineers utilize a diverse array of tools to manage and process data. These include programming languages like Python and SQL, data warehousing solutions like Snowflake and Amazon Redshift, and distributed computing frameworks like Apache Spark.

Other essential tools include Apache Kafka, ETL tools, and workflow orchestration platforms like Apache Airflow.

Source: Gemini AI Overview

Dr. Kirk Borne is the Chief Science Officer at DataPrime, Inc.  He is a sought-after global speaker on topics ranging from data mining, data management, big data analytics, data science, machine learning, artificial intelligence, internet of things, data-driven decision-making, modeling & simulation of dynamic systems to emerging technologies, future of work, education, and science.

Prior to this role, he was the Principal Data Scientist, Executive Advisor and the first Data Science Fellow at Booz Allen.

Kirk is also Founder and Owner, Data Leadership Group LLC.

George Mason University’s data analytics engineering programs at Volgenau prepare students for their future careers in a growing discipline.

All of our programs are taught by our industry-leading faculty members across schools and colleges in Mason, giving our students the ability to see the numerous possibilities a data-driven degree can offer.

• Master of Science –– The MS in data analytics engineering is a multidisciplinary degree program at the Volgenau School of Engineering. It provides students with an understanding of the technologies and methodologies necessary for data-driven decision-making.
• Certificate –– The graduate certificate in data analytics engineering gives students a foundation of basic data analytics and data science principles.
• Master of Science Online –– The online MS program gives students the flexibility to earn an advanced degree and expand their knowledge in data analytics in an asynchronous format.
• Certificate Online –– The online graduate certificate in data analytics engineering gives students a foundation of basic data analytics and data science principles with the flexibility of an online asynchronous format.

Data analytics engineering is an expanding field. Therefore, all our programs instruct students on current and innovative tools and prepare them to be adaptable to the future of the field.

Source: GMU

Disclaimer: The content in this post is from the Academy of Data Science website WITHOUT ANY EDITS. Virginia Tech is a public university in Southwestern Virginia, USA.

Virginia Tech’s Academy of Data Science was launched in 2020, in part to help meet the growing demand for workers who possess the skills to analyze data. Data science — a transdisciplinary field that draws upon the theories, methods, and concepts of statistics, mathematics, computer science, and information science to extract knowledge and insight from data — not only impacts all branches of science, but other fields as well.

The Academy of Data Science will focus on the development of methods, techniques, and tools for extracting knowledge and insight from data to further science. In doing so, it will elevate data science as a scientific discipline of its own, as well as bolstering the integration of data science into all scientific fields.  Additionally, the Academy will serve as the connective fabric between the College of Science and other Virginia Tech colleges and institutes as they collaborate to develop new data science methodologies and applications of data science in scientific disciplines.

Tom Woteki, a three-time Virginia Tech alum with a Ph.D. in statistics, was named the founding director of the Academy of Data Science. He also heads the part-time data analysis and applied statistics master’s degree program in the greater Washington, D.C., metro area.

Source: VT Website