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Blog
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Data Analysts: Who Are They and How to Find Them
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Introduction
- Data is collected by everyone, from stores and restaurants to monopoly companies owning apps with millions of users. A data analyst helps to make the information gathered useful for the business so that companies receive invaluable insights and make the right decisions.
Today we will tell you who these essential specialists are, what tasks they tackle and how companies should act in order to find the right talents for their projects.
At Gitmax, we employ more than four scores of such specialists who work on various outsourcing and custom development projects for our clients and daily help find right data-driven answers to exciting business questions.
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Who is a data analyst
- A data analyst is a specialist who collects, processes, studies and interprets various data daily gained by a company. The work of such specialists helps to make decisions in business and management. Typically, such specialists work in companies that employ a data-driven approach, making strategic decisions dependent on data analysis and its interpretation.
A data analyst is an important participant in a business with a deep understanding of business processes almost on the level of an owner of the company because the analyst's work results provide confidence for the decisions companies are about to make.
Creating a new product commonly requires a big budget, while making a mistake when implementing a new feature can cost a company reputation and profit. Data analysts conduct A / B tests and build various models, firstly, to check how users or customers react to new features and, secondly, to evaluate the prospects for a particular project. It not only reduces business risks but also costs less for the business. An essential asset for a Data Analyst in order to perform well is to understand business processes. Therefore, it is vital that he can affect the decision-making processes based on the results of his research, otherwise, the outcome of his/her works simply becomes useless.
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Data Analyst Tasks
A good data analyst is not just a mathematician with programming skills - (s)he understands business processes and knows the product or the service well, knowing what brings the business profit. As a result, the outcome of analysts' work can directly (or indirectly) bring companies higher revenue as well making users or customers happier.
In addition to various software tools, it is important for data analytics to develop data meta-professional skills that assist in doing their job better. Such skills include the ability to establish communication with colleagues and other stakeholders, the ability to solve problems and mitigate conflict situations with the least losses, as well as having a strong emotional intelligence. Such skills, of course, are more related to personality rather than to the hard skills, however, these soft skills can also be built and well developed.
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It is important not to confuse a data scientist with a data analyst. The first is an engineer with a knowledge of a certain set of languages and algorithms who fulfills the given technical problems by using sophisticated analytical programs, machine learning and statistical methods. Meanwhile, the latter one develops and tests hypotheses, providing answers to business needs, i.e. making use of the information. It is important for the analyst not only to correctly interpret the indicators, but also to properly visualize the outcome for further decision-making. In the work of data a nalysts, there is more communication with the customer than in the work of data scientists.
- The tasks of data analyst may vary from business to business, however, the overall routine picture of the analysts stays the same:
- Collecting data (forming a request himself or receiving a task from managers);
- Getting acquainted with the dataset parameters (what types of data are collected, how they can be sorted);
- Data pre-processing (cleansing, editing, wrangling);
- Interpreting the data (basically, solving business problem);
- Making a conclusion;
- Visualizing the outcome (in such a way, that it is visually clear which data-driven decision to make/ prove or disprove hypotheses).
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Skills and duties: what employers look for
- With each passing year, the demand for talented data analysts is growing faster than ever, while requirements alter as well.
Just about 10-15 years ago, a Data Analyst was believed to be a person who sits all day at the computer screen filling out Excel tables, copying data from one file to another, extending formulas a couple of lines further, saving and sending it all to the managers.
These tasks were repeated day after day, while all the creativity could have been put in writing a huge formula in Excel, which speeded up the work. Coupled with waiting for 5-10 minutes for the computer to process the information and calculate all the data, it was better to leave the PC alone and go drink tea for a bit.
- Today as the data is increasing by leap and bound, employers mostly want the Data Analyst to combine roles of an analyst, a database administrator, a developer, a Business Intelligence (BI) engineer, an ETL specialist, and with any luck, also a product manager.
The skill set has shifted towards hard skills, such as SQL, BI, Python, R, Java.In addition, the analyst must have experience with various products, such as Google Analytics, Search Console, Amplitude, Mixpanel, Hotjar, Google Ads, DoubleClick, etc.
- What’s also important:
- Building data warehouses (DWH);
- Having an experience in A/B testing as well as working with product hypotheses;
- Being able to read HTML and CSS code;
- Understanding marketing funnels and advertising campaigns.
Not to mention experience in Data Science, like building regressions, clusterings, correlations and forecasts, which will also be a plus.
That could be it, but soft skills are also required to be on a certain high level. That is absolutely fair as Data analysts often unites business and software development, that is why they must be stress-resistant, business-oriented, persistent and unresentful. After all, most of the time they are occupied communicating with developers, database administrators, and engineers, who, in turn, expect that if you come to them with a task, the level of your knowledge should not be lower than a Middle Full Stack developer.
That could be it, but soft skills are also required to be on a certain high level. That is absolutely fair as Data analysts often unites business and software development, that is why they must be stress-resistant, business-oriented, persistent and unresentful. After all, most of the time they are occupied communicating with developers, database administrators, and engineers, who, in turn, expect that if you come to them with a task, the level of your knowledge should not be lower than a Middle Full Stack developer.
- Equally important is the ability to present the results, draw conclusions based on the metrics, give advice on business improvement and conduct deep research, for example, of the competitors or the market.
Our expertise and experience shows that employers are rarely looking for freshly-entered the-market analysts. More often, they need a specialist with two-three years of experience as companies simply do not have those who will train a junior analyst. It is him instead who should teach the team how to make data-driven decisions.
That is not surprising that companies now face a shortage of specialists who meet all these requirements. Many startups and small companies want to find one person who will lead marketing, product and web analytics, develop a data warehouse, write ETL processes and implement BI systems. It can take up to 9 months to find such a candidate who is ready to work without a team.
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What should you do to find your specialist
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- Don’t focus on unicorns.
- Try to highlight key characteristics for the candidate.
- Don't be afraid to spend time communicating with a large number of candidates.
- Imagine if you hired an employee solely based on his hard skills and test assignment, but then it turned out that the specialist could only perform the assigned tasks. That’s why at GitMax, we suggest our clients to better “forgive” the candidate for his lack of specific technical skills, and rather focus on his сuriosity, initiative and openness. Tag Manager and Google Analytics skills can be improved in a month, but motivation is way much more difficult to find.
Devise pre-hire assessment tests
Devise pre-hire assessment tests
The tasks do not need to be based on the bottlenecks of your analytics, as it is difficult for a new person to understand that you hid the Chinese encoding in the test dataset in line 100001, which eventually spoils the entire analysis. Give general tasks aimed at testing logic and hard skills (you may ask for an opinion, advice or ask to draw some conclusions). Once there was a case when one of the companies complained that candidates did not perform well on the assessment test. It turned out that the employer made a mistake in the description of the database, and even the most brilliant analyst could not tackle the task as it was required.
See the person behind the file with the test. Unfortunately, there are companies who can put 20 questions in the pre-hire assessment test which will take a minimum 15 hours to complete. If those questions also do not relate to the description of the vacancy, it’s a bingo for “How to lose a candidate”. Do not bring out all backlog tasks into the test, find a balance.
And keep in mind asking the candidate about his plans. Imagine, that you found a candidate that is tailor-made for the role and you are about to send him an offer. But when you asked him about his plans, the specialist replied: “Well, in six months, I would like to switch to a product manager position. I heard that horizontal movement is common in your company”.It is crucial to find out what a candidate is interested in, in what direction he wants to develop and whether these plans coincide with yours. There is nothing wrong with letting a candidate move to product management. However, if you have already spent about six months looking for the fit, then you’d spend another three months on training, and next quarter he will ask for the movement, we’d say you need to decide if you are ready to start the search all over again.
See the person behind the file with the test. Unfortunately, there are companies who can put 20 questions in the pre-hire assessment test which will take a minimum 15 hours to complete. If those questions also do not relate to the description of the vacancy, it’s a bingo for “How to lose a candidate”. Do not bring out all backlog tasks into the test, find a balance.
And keep in mind asking the candidate about his plans. Imagine, that you found a candidate that is tailor-made for the role and you are about to send him an offer. But when you asked him about his plans, the specialist replied: “Well, in six months, I would like to switch to a product manager position. I heard that horizontal movement is common in your company”.It is crucial to find out what a candidate is interested in, in what direction he wants to develop and whether these plans coincide with yours. There is nothing wrong with letting a candidate move to product management. However, if you have already spent about six months looking for the fit, then you’d spend another three months on training, and next quarter he will ask for the movement, we’d say you need to decide if you are ready to start the search all over again.
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Conclusion
- As you can see, a data analyst calls for natural curiosity, honed communication skills, a flair for numbers, and a strive for problem solving. And if your company is looking for such talents or tech specialists of any other profile, drop us a line - we will find you the most suitable candidates for your projects.
Let's work together!
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