Data analysts work in various sectors, focusing on making sense of an organisation's data. Their role is highly specialised, involving the practical application of data modelling, statistics, and reporting in visual and written format.
Good data analysts have the ability to work with large datasets, applying relevant and appropriate statistical techniques to manipulate and interpret the data into meaningful and useful information.
Their work is becoming increasingly important in today's digital world, where organisations rely on data to help them make informed decisions on performance and future direction.
Data analysts are at the heart of an organisation, and recruiting the right people for this highly specialised role is essential if an organisation is to make sense of the data it produces and use it to its full potential.
This article explores some of the skills familiar to those that excel as data analysts. You will also learn about some pre-employment assessments that you can use in your recruitment process to test for these skills.
What should a data analyst be able to do?
The duties of a data analyst are focused on making sense of the data a company produces. Data analysts can work across all sectors, including the public sector, where the data they work with is focused on an industry rather than a specific organisation.
No matter the focus of data, data analysts use their specialist understanding of programming languages, statistical analysis, and data modelling to select the appropriate method to analyse data sets. This can include taking large amounts of raw data and cleaning up the data into a more usable format before analysing and manipulating the data using relevant modelling techniques.
They may also choose to sample data rather than analyse whole data sets, comparing data modelling techniques and results to identify variances in data and the validity of the results gained.
Once the data has been analysed, data analysts need to interpret the results to make sense of the data, transforming it into a format, whether that be visual or written, that others can understand.
Data analysts need to keep in mind the purpose of their analysis, ensuring that the interpretation and explanation of the results are relevant and can be used to inform decisions.
They report on the results of their analysis, and any follow-up analysis and share their recommendations for use by stakeholders within the business.
Skills to look for in a data analyst
Data analysts need a specific set of skills to carry out their roles effectively. As a recruiter, it is essential to assess candidates against these skills to ensure you are hiring the best candidates from your applicant pool.
Problem-solving skills: a data analyst must be able to use the data they have gathered, and the results gained to solve business problems. Using their analytical and critical thinking means they can make sense of the data, determine relationships between data to evaluate options, and determine solutions.
Reading comprehension: having the skill to read, understand, and interpret written information enables data analysts to understand the purpose of their analysis and represent their findings in a way that others can understand.
Written skills: while the duties of a data analyst mostly focus on making sense of data through statistical analysis, a large part of their role involves the communication of their findings to those who are less versed in data analysis. Sharing the critical points of their findings and recommendations in writing means that others can use their work for data-driven decision-making.
Software skills: data analysts use various software programmes to perform their statistical analyses. Being confident in using different software and demonstrating IT literacy skills in learning any new software allows them to use relevant and up-to-date programming analysis tools for their company's data.
Decision-making skills: being able to make decisions based on the results gained from their analysis is a crucial part of the role of a data analyst. They need to evaluate the possible options, weigh up options, and decide on the best solution to recommend to their stakeholders.
Useful abilities for a data analyst
In addition to a robust set of skills, data analysts need to draw on both technical and inherent abilities. When shortlisting applicants, it is essential to look for the following abilities:
Integrity: data analysts deal with sensitive data and must show integrity and honesty. They also need to take ownership of the decisions they make given recommendations they share with their stakeholders may be used to inform wide-reaching organisational decisions.
Originality: Being creative in their analysis and thinking of different ways to analyse or present data allows data analysts to stay at the forefront of their profession. This means their company gains a competitive advantage through their data-driven approach to decision-making.
Critical thinking: the ability to think critically and apply analytical and logical reasoning to analysis and interpretation is a must for data analysts. The ability to question data and make logical conclusions means data analysts can make the most of the data they are working with.
Numerical reasoning: data scientists work with all data types, applying statistical and mathematical formulas to analyse data sets. Having strong numerical reasoning is essential for all data scientists to fulfil their roles.
Oral expression: conveying the results and recommendations gained from analysis in a clear, concise, and easy-to-understand way is vital if the recommendations made are to be taken on board by stakeholders. Where there is resistance, data analysts need to use persuasive language to ensure that the analysis is clearly understood.
Which soft skills tests could I use to hire a data analyst?
Determining whether candidates have the soft skills required for a role can be difficult from a resume or interview alone.
Using pre-employment tests in your recruitment process helps gain a better understanding of applicants' soft skills when it comes to those needed to be a data scientist.
Accountability: a scenario-based test that looks at whether individuals demonstrate integrity and responsibility in their role. This test also helps you understand whether candidates will be a good fit for the position based on their ownership of decisions.
Communication skills: this test assesses candidates' active listening, written and verbal communication skills, and ability to pick up on non-verbal cues.
Decision-making: in this test, individuals must consider the different scenario-based questions and use their critical thinking and analytical skills to determine the course of action based on their given information.
Which technical or aptitude tests could I use to hire a data analyst?
The work of a data analyst draws on several technical skills and abilities, all of which are critical if the data being worked on is analysed to its full potential. When recruiting for data analyst roles, it is essential to assess candidates against the following abilities:
Numerical Reasoning: this timed test evaluates candidates' ability to work with numerical data to solve problems. Candidates are assessed on whether they can use basic mathematical principles to analyse, interpret and draw conclusions from numerical information.
Logical Reasoning: a test that requires candidates to use their problem-solving skills to identify patterns or relationships in data, then use what they have learned to determine which solution is correct.
Abstract Reasoning: assessing an individual's aptitude for problem-solving when using abstract information. This test requires candidates to think laterally, logically, and creatively to determine relationships between sequences or patterns in data.
Verbal Reasoning: assessing an individual's understanding of written words and expressions and whether they can interpret the information they have read and use what they have learned to solve problems.
Microsoft Excel: proficiency in Microsoft Excel is a must for all data analysts. This test enables you to gain a practical insight into whether candidates can use the application and its functions to analyse data sets adequately.
Our recommended test battery for a data analyst
To ensure you recruit suitable candidates who demonstrate the necessary skills and abilities to be a successful data analyst, we recommend using the following test battery in your recruitment process.
Numerical Reasoning: a timed test to assess whether candidates are comfortable working with numerical data to solve problems. This test also gives you an insight into whether candidates can work under pressure.
Abstract Reasoning: a test of a candidate's ability to think fluidly and laterally when faced with abstract information problems. This test also requires candidates to draw on their logical reasoning and creativity.
Accountability: demonstrating integrity and taking ownership of their decisions is essential for any data analyst. Using scenario-based questions, this test determines whether candidates are a good fit for the role and organisation.
Communication Skills: evaluate candidates on all aspects of their verbal and written communication skills, their ability to judge situations, and pick up on non-verbal cues when communicating with others.
Microsoft Excel: the Excel test helps you determine an individual's skill level when using Microsoft Excel as it is used by a data analyst frequently during day to day tasks.
For more information on hiring a data analyst, visit Picked's data analyst test page.