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data analytics, general

data analytics, general

Types of Degrees data analytics, general Majors Are Earning

Students pursuing data analytics, general may pursue degrees at several award levels.

Award Level Graduates
Certificate 2
Associate’s Degree 8
Bachelor’s Degree 172
Master’s Degree 1,491

What data analytics, general Majors Need to Know

Coursework for data analytics, general build a specific mix of knowledge, skills, and abilities — derived from O*NET surveys of workers in occupations that data analytics, general graduates commonly enter.

Knowledge Areas

Coursework in data analytics, general emphasizes the following knowledge areas: Knowledge areas for data analytics, general majors

  • Computers and Electronics — Importance 4.2 / 5; level 5.3 / 7.
  • English Language — Importance 3.9 / 5; level 4.5 / 7.
  • Mathematics — Importance 3.8 / 5; level 4.7 / 7.
  • Administration and Management — Importance 3.3 / 5; level 3.7 / 7.
  • Customer and Personal Service — Importance 3.3 / 5; level 3.8 / 7.

Importance is rated 1–5; level is 1–7. Source: ONET Online — weighted across related occupations.*

Skills

Skills built by a data analytics, general program reflects the day-to-day work of related occupations: Skills for data analytics, general majors

  • Critical Thinking — Importance 3.9 / 5; level 4.2 / 7.
  • Active Listening — Importance 3.9 / 5; level 4.0 / 7.
  • Reading Comprehension — Importance 3.8 / 5; level 4.1 / 7.
  • Speaking — Importance 3.7 / 5; level 3.9 / 7.
  • Complex Problem Solving — Importance 3.7 / 5; level 3.9 / 7.

Abilities

Innate abilities most relevant to data analytics, general careers — again drawn from O*NET surveys of related occupations: Abilities for data analytics, general majors

  • Written Comprehension — Importance 4.0 / 5; level 4.3 / 7.
  • Oral Comprehension — Importance 4.0 / 5; level 4.4 / 7.
  • Inductive Reasoning — Importance 3.9 / 5; level 4.2 / 7.
  • Oral Expression — Importance 3.9 / 5; level 4.4 / 7.
  • Deductive Reasoning — Importance 3.9 / 5; level 4.3 / 7.

Common Job Activities

Day-to-day, data analytics, general graduates report doing:

Activity Frequency / Importance
Working with Computers 4.7 / 7
Analyzing Data or Information 4.5 / 7
Getting Information 4.5 / 7
Processing Information 4.5 / 7
Communicating with Supervisors, Peers, or Subordinates 4.3 / 7
Making Decisions and Solving Problems 4.3 / 7
Updating and Using Relevant Knowledge 4.1 / 7
Interpreting the Meaning of Information for Others 4.1 / 7
Identifying Objects, Actions, and Events 4.0 / 7
Thinking Creatively 4.0 / 7

Technology Skills Used on the Job

Most frequently-cited tools used by data analytics, general professionals:

Tool / Software Category In-Demand
Microsoft Excel Spreadsheet software
C++ Object or component oriented development software
Microsoft Access Data base user interface and query software
IBM SPSS Statistics Analytical or scientific software
Microsoft Office software Office suite software
Structured query language SQL Data base user interface and query software
Microsoft SQL Server Data base user interface and query software
Microsoft PowerPoint Presentation software
SAS Analytical or scientific software
Teradata Database Data base management system software
C# Object or component oriented development software
Oracle Java Object or component oriented development software

Source: ONET Online technology skills, weighted across related occupations.*

Sample Job Titles

Real job postings for data analytics, general graduates include:

  • Data Analyst
  • Program Analyst
  • Reports Analyst
  • Business Process Analyst
  • Business Consultant
  • Business Analyst
  • Business Systems Analyst
  • University Professor
  • Project Management Professor
  • Flight Simulator Teacher
  • University Teacher
  • Instructor
  • Weight Control Lecturer
  • Military Science Instructor
  • Interdisciplinary Professor

Education Typically Required

Across the occupations open to data analytics, general graduates, the typical level of education actually held by current workers is distributed as:

Education Level Share of Workers
Bachelor’s degree 65.0%
Master’s degree 20.8%
Associate’s degree (or other 2-year) 4.8%
Post-baccalaureate certificate 3.6%
Some college courses 3.1%
Doctoral degree 2.1%
Post-doctoral training 0.6%
Education levels for data analytics, general majors

Source: ONET Online education / training / experience requirements.*

Who Is Earning a Degree in data analytics, general?

Gender Distribution

This field has a relatively balanced gender distribution: 41.9% women and 58.1% men among data analytics, general graduates.

Gender Graduates Share
Women 701 41.9%
Men 974 58.1%

Racial-Ethnic Diversity

At the national level, the racial-ethnic distribution of data analytics, general graduates is as follows:

Racial-ethnic diversity of data analytics, general graduates
Race / Ethnicity Graduates Share
White 638 38.1%
Asian 142 8.5%
Hispanic or Latino 126 7.5%
Black or African American 102 6.1%
American Indian / Alaska Native 6 0.4%
Two or More Races 41 2.4%
Race Unknown 52 3.1%
International Students 568 33.9%

See minority definition below.

Online data analytics, general Programs

Fully online options are documented by IPEDS for data analytics, general. The table below shows how many graduates earned at least some of their coursework online (Distance-Ed Available) versus completing the entire program online (Distance-Ed Only).

Award Level Distance-Ed Available Distance-Ed Only
Associate’s 2 0
Bachelor’s 7 3
Master’s 15 8

Distance-Ed Only = degrees completed entirely online; Distance-Ed Available = degrees including at least some online coursework. Source: IPEDS Completions by Distance Education status.

You may also be interested in these closely related fields of study:

Program CIP Code
Data Analytics 30.71
Business Analytics 30.7102
Data Analytics, Other 30.7199
Data Visualization 30.7103
Financial Analytics 30.7104
Computational Science 30.3001
Data Science, General 30.7001
Data Science, Other 30.7099

References

The racial-ethnic minorities count is calculated by taking the total number of students and subtracting white students and international students. This number is then divided by the total number of students to obtain the racial-ethnic minorities percentage.

More about our data sources and methodologies.

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