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Data Management
and Engineering

The definition for Data Management and Engineering as developed by approximately 100 Thought Leaders (mostly Chief Technology Officers and Chief Information Officers) through three meetings and follow-up surveys to gain consensus is:

Data Management and Engineering typically utilizes specialized software to store, organize and secure data in both relational databases and in other non-relational formats. It includes capacity planning, installation, configuration, database design, migration, performance monitoring, security, troubleshooting, as well as backup and data recovery. —This definition was adapted from Wikipedia.

After the “thought leader” meetings, subject matter experts (SMEs) for this “Data Analytics and Predictive Modeling” cluster were recruited to attend meetings held to discuss, rank, and revise a pro-forma list of tasks, knowledge, skills, and abilities. The meeting discussion and vote results were synthesized and presented again to the SMEs who participated in the meetings for verification.

Each document below is considered a draft.

Anyone can access the material by clicking in the table below – online viewing via the “Section” column and PDF/Excel downloads via the “Downloads/Documents” column. To be able to comment on the various documents you will need to click on the “Sign in” link in the “Comments/Access” column.

Note: The goal of this grant is to consider these all “living documents” subject to ongoing revision quarterly based on additional SME comments submitted below. While the time required to provide SME comments may vary, the estimated completion time for all 4 sections below is 45- 60 minutes. SMEs can choose which sections to comment on.

 

*Anyone is welcome to use, modify, and/or distribute ITSS findings and data, but you must give clear attribution to the source of this material by citing “IT Skill Standards 2020 and Beyond (NSF ATE project grant DUE 1838535).”

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