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Method: "Data Engineering" Home Page
| ATTRIBUTE NAME |
ATTRIBUTE VALUE |
| Title: |
Data Engineering |
| Abbreviation: |
DE |
| Similar Method: |
Data Science |
| Description: |
Data Engineering, which is separate from but intersects with Data Science, is the very complex practice of methodically applying processes, tools and technologies to solve data, information and knowledge problems. Unlike many theoretical methods, Data Engineering always focuses on producing tangible outputs that can be delivered, operated, supported and (most importantly) continuously improved.
Data Engineers often have a very wide array of knowledge related to many different data processing and manipulation technologies, understanding how and when to use them, how to connect them together, how to package them, how to deliver them, how to operate them, how to support them, and how to optimize them. Most importantly, Data Engineers spend a great deal of time understanding funding, costs, and Return on Investment (ROI) for data related solutions (both software and hardware solutions). |
| Read More: |
https://scholar.google.com/scholar?q=%22Data+engineering%22&btnG=&hl=en&as_sdt=0%2C31 |
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