How to Move From Data Analyst to Data Quality Analyst

Moving from Data Analyst to Data Quality Analyst could open up long-term opportunities


“you need to understand the importance of continuous improvement and other core quality activities”

— Dylan Jones


If I search for “Data Analyst” practitioners in my UK LinkedIn network I get just under 4,000 people in the search results. A search for “Data Quality Analyst” finds about 200 people.

Clearly, there are far more data analyst roles out in the marketplace but this obviously brings a greatly increased level of competition.

If you’re working as a data analyst perhaps it’s time to shift your focus to data quality analyst roles to help increase your career potential? If that’s something you’ve considered then the next question you’ll pose is what additional skills will I need?

Fortunately you’ll find that many of your data analyst skills are exactly what companies are searching for in a data quality analyst.

Data Analyst Skills for Data Quality Roles

Here are some common data analyst skills I discovered in a recent survey of data analyst roles:

  1. Handle large and complex datasets in different formats
  2. Analyse and interpret data, producing clear and compelling reports for different audiences
  3. Create, document and analyse data models
  4. Test and verify processes and systems to understand the cause of data issues
  5. Create code and analysis scripts in SQL and Excel
  6. Statistically analyse data and interpret findings
  7. Quickly identify people, process, and systems insights to pursue
  8. Concisely summarize and communicate recommendations to various levels of management
  9. Identify opportunities for product improvements
  10. Manipulate data and understands the underlying process details
  11. Create and maintain detailed documentation
  12. Adhere to standard operating procedures
  13. Analyse problems and errors produced by business applications
  14. Coordinate various business improvement initiatives
  15. Must have excellent analytical and problem resolution skills
  16. Must have excellent interpersonal, organizational, and verbal and written communication skills

All of those skills are textbook Data Quality Analyst skills to have so if you’re considering a move into a Data Quality Analyst role in the future your focus must be on refining each skill listed and extending your current performance.

If you’re used to analysing one type of business data, get experience with more varied types from different departments. If you’ve only ever used one type of tool for analysis e.g. SQL, try your hand at different products.

Master Quality Principles

With a solid bedrock of data analyst skills you can then start to build a grounding in quality principles.

For example, you need to understand the importance of continuous improvement and other core quality activities. This is what distinguishes you from the Data Analyst who may perform one-off activities or not fully understand the bigger picture of how their actions impact the wider enterprise.

Tip: Information Quality Applied by Larry English provides one of the more quality focused books available, drawing on many of the principles first cited by Deming etc.

Data Quality Technology Skills Are Important

Next, you’ll need to get to grips with modern data quality software as that is a common requirement in most organisations when hiring a new Data Quality Analyst. If you don’t have that experience, don’t worry, there is free software available on Data Quality Pro to support you and get you started.

In order for you to gauge the quality of data and spot where best to make improvements you next need to understand the importance of data quality rules and measures. We often call these measures “dimensions” because they help us quantify issues against the different characteristics required of our data. Software can help but many dimensions are subjective so require distinctive techniques such as surveys and interviews with staff to quantify the impacts.

Tip: Two useful books in particular for rules, measures and dimensions are Data Quality Assessment by Arkady Maydanchik and Executing Data Quality Projects by Danette McGilvray.

Show Us The Money

Armed with your assessment of the data you can then start to infer the impact on the business and create a business case for improvement. This is often a skill lacking in the Data Analysts’ arsenal. With this comes the need for root-cause analysis because only when you understand the impact and cause can you develop a comprehensive business case for improvement.

Data Quality Improvement Requires Process Change

Process improvement then becomes a big part of the Data Quality Analyst role and often a major difference with the more junior Data Analyst positions. The causes of poor data are often varied so strong communication and even political skills are required as you strive to help the organisation mature or transform some part of its technology, process or organisational makeup.

Here To Support You

These are just some of the differences between a Data Analyst and Data Quality Analyst role.

For anyone seeking to move into a more Data Quality focused position why not become a member (it’s free) and reach out, we’re happy to help you make that transition and point you to a range of free software and tutorials to make the process less arduous.

Just contact us for details

Comments are closed