data analysttodata quality specialist
A data analyst already meets 67% of what the data quality specialist role asks for. The move turns on 6 required skills not yet in the profile.
67%
38.4/ 100
1 Share of the data quality specialist role’s weighted skill requirement already met by the data analyst profile. Required skills count in full, supplementary skills at 0.35. Directional: the figure for the reverse move differs. 2 Combines what is missing with how specialised it is, so a gap of general skills scores easier than the same number of narrow ones.
Why this move works
A data quality specialist role treats 14 of its required skills as things a data analyst already does. These are the ones it depends on most.
- data ethics
- database
- define data quality criteria
- establish data processes
- handle data samples
- implement data quality processes
What stands in the way is 6 required skills the profile does not yet cover. Table 3 groups them; Table 4 says which to take first.
Table 2 · What you already bring
Of the 26 skills that carry over, these are the ones fewest other occupations ask for. A data quality specialist role needs them, and most people applying for one will not have them already. This is the part of a data analyst background worth leading with.
- already held handle data samples information skills
- already held data ethics arts and humanities
- already held normalise data working with computers
- already held healthcare analytics health and welfare
- already held implement data quality processes working with computers
- already held perform data cleansing working with computers
All 26 carried skills, including the 14 the data quality specialist role treats as required.
Table 3 · What you would need to learn
The 14 missing skills fall into 5 areas of the ESCO skill hierarchy, numbered below in the order worth working in: the areas carrying the most required skills come first, and inside each one the required skills sit above the supplementary ones.
- required, not held design database scheme required
- required, not held address problems critically required
- optional, not held design database in the cloud optional
- optional, not held build business relationships optional
- optional, not held train employees optional
- required, not held manage database required
- required, not held process data required
- optional, not held execute ICT audits optional
- required, not held manage standards for data exchange required
- optional, not held manage schedule of tasks optional
- optional, not held perform project management optional
- required, not held utilise regular expressions required
- optional, not held perform data analysis optional
- optional, not held business processes optional
Table 4 · Where to start
The 3 entries a data quality specialist role is least likely to hire without. The ordering is computed from the skill data, not from what pays.
- 01 utilise regular expressions skill · occupation specific
- 02 design database scheme skill · sector specific
- 03 manage standards for data exchange skill · sector specific
Each entry opens a course search for that skill. Career Overlap earns nothing from these links.
Appendix · The rest of the record
All 26 skills that carry over
- already held data ethics knowledge
- already held database knowledge
- already held define data quality criteria skill
- already held establish data processes skill
- already held handle data samples skill
- already held implement data quality processes skill
- already held information structure knowledge
- already held manage data skill
- already held normalise data skill
- already held perform data cleansing skill
- already held query languages knowledge
- already held report analysis results skill
- already held resource description framework query language knowledge
- already held use data processing techniques skill
- already held LDAP knowledge
- already held LINQ knowledge
- already held MDX knowledge
- already held N1QL knowledge
- already held SPARQL knowledge
- already held XQuery knowledge
- already held data engineering knowledge
- already held data quality assessment knowledge
- already held execute analytical mathematical calculations skill
- already held healthcare analytics knowledge
- already held statistics knowledge
- already held visual presentation techniques knowledge
8 supplementary skills, helpful but not required
- optional, not held design database in the cloud optional
- optional, not held execute ICT audits optional
- optional, not held build business relationships optional
- optional, not held business processes optional
- optional, not held manage schedule of tasks optional
- optional, not held perform data analysis optional
- optional, not held perform project management optional
- optional, not held train employees optional
41 held skills the data quality specialist role does not ask for
- not needed by the target role Hadoop knowledge
- not needed by the target role analyse big data skill
- not needed by the target role apply statistical analysis techniques skill
- not needed by the target role business analytics knowledge
- not needed by the target role business intelligence knowledge
- not needed by the target role cloud technologies knowledge
- not needed by the target role collect ICT data skill
- not needed by the target role create data models skill
- not needed by the target role data mining knowledge
- not needed by the target role data models knowledge
- not needed by the target role data science knowledge
- not needed by the target role data storage knowledge
- not needed by the target role data visualisation software knowledge
- not needed by the target role deliver visual presentation of data skill
- not needed by the target role digital data processing skill
- not needed by the target role documentation types knowledge
- not needed by the target role game theory knowledge
- not needed by the target role gather data for forensic purposes skill
- not needed by the target role image recognition knowledge
- not needed by the target role information architecture knowledge
- not needed by the target role information categorisation knowledge
- not needed by the target role information confidentiality knowledge
- not needed by the target role information extraction knowledge
- not needed by the target role integrate ICT data skill
- not needed by the target role interpret current data skill
- not needed by the target role make data-driven decisions skill
- not needed by the target role manage cloud data and storage skill
- not needed by the target role manage data collection systems skill
- not needed by the target role manage quantitative data skill
- not needed by the target role marketing analytics knowledge
- not needed by the target role multidisciplinary research knowledge
- not needed by the target role online analytical processing knowledge
- not needed by the target role perform data mining skill
- not needed by the target role research design knowledge
- not needed by the target role social network analysis knowledge
- not needed by the target role statistical modeling techniques knowledge
- not needed by the target role store digital data and systems skill
- not needed by the target role unstructured data knowledge
- not needed by the target role use databases skill
- not needed by the target role use spreadsheets software skill
1 further entry not listed here
1 gaps that are knowledge rather than practice
Knowledge gaps usually close through study. Practical skill gaps usually need something you can point at.
- optional, not held business processes optional
Other moves recorded from data analyst
- data entry clerk 63% covered · moderate
- chief data officer 56% covered · moderate
- ICT information and knowledge manager 50% covered · substantial
- data entry supervisor 49% covered · substantial
- data engineer 47% covered · substantial
- data scientist 47% covered · substantial
- computer vision engineer 43% covered · substantial
- big data archive librarian 32% covered · career change
How this record was compiled
Both occupations are taken from ESCO, which lists the skills and knowledge each occupation is expected to have and marks every one required or optional. Nothing here is a prediction about hiring, and nothing here knows that a particular employer wants a particular certificate. Treat Table 3 as a starting point for your own research rather than a syllabus. The full method states what these figures can and cannot tell you.