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Data Analyst (Korea)

💼 Business By CampusDown Wiki Editorial Team Last updated
Answers business questions with SQL, statistics and visualisation; distinct from data scientists and engineers.
Contents
  1. 1. History and scholarship
  2. 2. What the job involves
  3. 3. Hiring and careers
  4. 4. FAQ
  5. 5. References

History and scholarship

Modern statistics builds on Ronald Fisher (1925). John Tukey's 'The Future of Data Analysis' (1962) and EDA (1977) defined data analysis as its own field. Codd's relational model (1970, CACM) underlies SQL; Breiman (2001) contrasted 'two cultures'; Davenport and Patil (2012, HBR) heralded data roles; Wickham (2014) and Donoho (2017) extended the scholarship.

What the job involves

Metric design, dashboards, SQL, statistics and A/B tests, visualisation and stakeholder communication. Scope and required skills vary by company and industry; check actual job postings and NCS job descriptions.

Hiring and careers

SQLD, ADsP and Big Data Analyst support applications; portfolios matter. Works with performance marketing.

FAQ

Is Python required?
SQL is basic; Python/R varies.
Need a stats degree?
No, but basic statistics is needed.

Sources reviewed: 2026-10-26

References

  1. Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver & Boyd.
  2. Tukey, J. W. (1962). The future of data analysis. Annals of Mathematical Statistics, 33(1), 1–67.
  3. Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley.
  4. Codd, E. F. (1970). A relational model of data for large shared data banks. Communications of the ACM, 13(6), 377–387.
  5. Breiman, L. (2001). Statistical modeling: The two cultures. Statistical Science, 16(3), 199–231.
  6. Davenport, T. H., & Patil, D. J. (2012). Data scientist: The sexiest job of the 21st century. Harvard Business Review, 90(10), 70–76.
  7. Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59(10), 1–23.
  8. Donoho, D. (2017). 50 years of data science. Journal of Computational and Graphical Statistics, 26(4), 745–766.
  9. 국가직무능력표준(NCS). https://www.ncs.go.kr
  10. 고용24 직업정보(고용노동부·한국고용정보원). https://www.work24.go.kr

Reports and materials that use this theory (Korean)

There are no materials dedicated to this theory yet, but you can search related reports in the CampusDown library (Korean).

Find more reports · Search '데이터 분석가' on CampusDown →
ADsPADsP is Korea's state-recognized data analytics semi-professional certification. Covers its three subjects, 50 questions in 90 minutes, the pass mark and how it compares with SQLD and the Big Data Analysis Engineer qualification.📚 EducationSQLDSQLD is a state-recognized SQL developer certification run by the Korea Data Agency. Covers the two-subject, 50-question, 90-minute format, the 60-point pass mark with a 40% per-subject cutoff, SQLP and a study order for non-majors.📚 EducationEngineer Big Data AnalysisEngineer Big Data Analysis is a Korean national technical qualification created in 2020 and administered by the Korea Data Agency. Covers the four-subject written exam, the 180-minute integrated practical with coding tasks, pass marks and preparation.📚 EducationSocial Survey Analyst (Korea)Korea's Social Survey Analyst is a national technical qualification covering survey design and statistical analysis. Covers levels 1 and 2, eligibility, the three written subjects, the practical exam and research-job use.📚 EducationPerformance Marketing (Korea)Performance marketing runs digital ads against measurable outcomes and optimises budgets with data. Covers measured-advertising history, ad-auction and experiment research, and careers in Korea.💼 BusinessMarketing Job (Korea)Marketing roles analyse markets and customers to plan and run product, price, channel and communication strategy. Covers the scholars behind marketing theory, sub-roles and entry prep in Korea.💼 Business

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This article was last updated on October 26, 2026. It is based on widely recognized original works and textbooks; when citing it in a paper, please check the original sources listed in the references.