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Data Engineering 2

 Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. It is a broad field with applications in just about every industry. Organizations have the ability to collect massive amounts of data, and they need the right people and technology to ensure it is in a highly usable state by the time it reaches data scientists and analysts.


Data Engineers maintain the data infrastructure to support business applications. As part of their responsibilities, they fuel Artificial Intelligence analytics and the Machine Learning process.

Various positions held by a Data Engineer are listed below.

  • Data Architects ingest, design, and manage the sources of data essential for business insights to build a Data Engineering architecture. With in-depth knowledge of SQL and XML, they can integrate and organize certain parts of the data management system.
  • Data Engineers are the ones who need to be proficient in programming languages such as Python and Julia. They design, integrate, and prepare the data infrastructure, adhering to all data management norms.
  • Database Administrators (DBAs) design and maintain database systems to ensure that users can access all functions seamlessly. They also optimize the speed of databases and work against workflow interference.


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