The Data Analyst is a fundamental professional figure for digital marketing and is highly sought after by companies nowadays.
Anyone with a technological tool that has access to an Internet connection is surfing the net. The world population is always online: millions of users access the web every day and spend their time interacting on social networks, browsing and reading posts on Facebook, Instagram, or WhatsApp, or buying goods and services.
Every day a huge amount of data is generated which becomes a gold mine for companies, which offer their products on the market. These Big Data require specific analysis techniques and suitable technologies to obtain the information that is needed for a company’s business.
To do this, figures are needed who are capable of understanding its complexity by making use of specific and targeted research tools.
This is where the figure of the Data Analyst comes into play, literally Analyst of Data, a very popular profession, as the data on the market constitutes the new “black gold” for companies. He is like the radar or GPS for an ocean liner. Of course, some daredevils still sail by sight, but in the business world, sailing by sight is often synonymous with failure.
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What does a Data Analyst do?
Precisely the Data Analyst deals with analyzing and interpreting the data at his disposal to understand useful information for the business of an activity, and anticipating future trends. Optimal data analysis will show a clear picture of where you are, where you’ve been, and where you should go.
It is one of the most popular digital professions and its work is essential for developing theories that can bring tangible benefits and, overall, allow management to make data-driven decisions, i.e. to choose solutions based on objective arguments and not on sensations personal.
By gathering this information, companies can have a deeper understanding of their industry, their audience, and their business as a whole.
The main tasks of the Data Analyst are:
- understand the type of research to be carried out;
- analyze the data according to the different sources from which they come;
- select the useful ones;
- organize data and create clusters;
- check the quality of the data, detect errors in the collection, and if there are any duplicates (data cleaning);
- interpret data to identify trends and patterns through statistical models;
- create and update reports;
- communicate and present the results of the analysis to company managers and executives through the use of reports, tables, and graphs.
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Skills of the Data Analyst
The Data Analyst is concerned with understanding and drawing insights, and intuitions, from the data. You work closely with the managers of the company departments, with the Project Managers and Data Scientists trying to solve the problems that slow down the company’s business by bringing solutions through the analysis of information.
The data to be processed come from various sources and have different forms they can be alphanumeric values, photos, videos, or documents that must be organized in such a way as to allow comparison and analysis.
For this reason, the main requirements of a Data Analyst, useful for filling his professional background, are:
- preparation in statistics and mathematics;
- knowledge of programming languages (SQL, Python, SAS, R, VBA);
- mastery of Excel worksheets;
- knowledge of DBMS (Database Management System);
- familiarity with Data Visualization tools (Power BI, Tableau, IBM);
- ability to use Business Intelligence tools ;
- knowledge of the main web analytics software.
Instead, the soft skills most required of a professional in this sector are:
- analytical thinking;
- written and verbal communication skills;
- ability to work in a team;
- ability to work under pressure;
- the propensity for problem-solving.
Where does a Data Analyst work and how much is paid?
It is legitimate to ask where Data Analysts work, and in which place and context they work their magic with data. It is a professional figure in great demand by companies and lends itself to various employment opportunities even in different fields. The most sought-after sectors are information technology, telephony, e-commerce, banks and insurance companies, media and communication, healthcare and tourism, retail and large-scale distribution, transport and logistics, and public administration.
We also find consultancy firms specializing in Business Intelligence that provide challenging job opportunities for the data analyst. His work, therefore, can be carried out on-site or even remotely thanks to the continuous development of smart working.
The salary of a Data Analyst varies according to the experience accumulated, the geographical area where he works, and the study plan he attended during his training.
The data analyst profession offers a lucrative earning potential, with salaries ranging from a minimum of $14,000 per year to a maximum of $65,000 per year. This makes it a highly rewarding career choice in terms of financial compensation.
A Junior Data Analyst with less than 3 years of work experience can expect to earn an average annual salary of around $23,000. As they gain experience and progress in their career, a Senior Data Analyst with 10-20 years of experience can earn an average of $48,000. For those in the late-career phase with over 20 years of experience, the overall average salary can reach $51,300.
It is evident that the data analyst profession offers competitive compensation within the digital field, making it an attractive option for professionals seeking financial stability and growth.
Tips for Becoming a Data Analyst
Working as a Data Analyst is certainly the most suitable professional choice for those with a propensity for analytical and logical reasoning. You need to be curious and creative, answer questions and have the ability to solve business problems and challenges. His “investigative” side leads him to question the possible relationships that are created between the data to obtain useful information for the company’s business.
So what do you need to study to become a Data Analyst? Training is in first place and the answer to this question is quite broad: at the moment there is no standard method to become a data analyst, but rather different paths that can be taken to reach the goal.
To acquire important knowledge in the field of data analysis, for example, it is possible to undertake a three-year or master’s degree course in scientific subjects such as Statistics, Computer Science, Mathematics, Computer Engineering, and Data Science, but also a degree in Economics, Finance or Business Administration.
But not only. Since the data analysis sector is very vast, it is possible to become a Data Analyst without a specific degree, simply by enrolling in master’s or online professional training courses with certification to acquire the skills necessary to make a career in that area.
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Interview with a Data Analyst
Andrea Bonomi, a communication professional, has the pleasure of introducing and interviewing Doctor Martino Crippa, Statistician and Data Analyst, who currently works at MailUp.
Who is the Data Analyst?
The Data Analyst is a professional figure who always supports a team. The Data Analyst doesn’t exist without a company or a project to help or support. He is a curious professional who likes to understand, likes to receive questions, and tries to answer them with data.
What advantages does the Data Analyst bring to the company?
In a company that is assumed to be data-driven, as they say in English, which therefore moves through processes driven by data, the Data Analyst or Data Scientist exploits information that is sometimes more or less understandable or more or less usable, to answer questions, to help in processes, to give useful tools for making decisions, to understand if the actions taken by the company or by a business unit have a return and work compared to others.
The digital tools you use in your work?
The market offers many tools. The ones I use daily are data analysis tools that interface with various company databases. The case of the company I work for, MailUp, is many and some use large volumes of data. Mainly they are programming languages to go and fish the data and then aggregate it. From my experience, I have used software that comes from an American company called SAS, Software Analysis System, SQL, and then R programming, an open source programming language for statistical data analysis, and then various reporting software.
During the day there is also Excel, which in some way, as a palette, can be combined. I would say that these are the essential tools, then depending on who sells one database rather than another, something may vary.
Python is another tool that is getting into the field a lot and I hope to use it sooner or later. I know that there are many tools for analyzing data in the digital field, from Google Analytics to Facebook Analytics, etc. In the case of the work I’ve done, both as a former Data Analyst Consultant and for what I do now, we prefer to download the data and bring it into company systems to be able to cross-reference more information.
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How to Become a Data Analyst?
To become a Data Analyst, at a training, educational, and university level, there are many paths. I have a degree in Statistics. I know that now many faculties and online courses are springing up that offer mixed Data Science paths, which cross several disciplines, a computer science part, a statistical part, and a mathematical part.
Let’s say that the road is long, this certainly. As one of my former employers used to say, being a data analyst is not a journey, it’s like climbing a mountain. In the sense that you often find yourself with incredible panoramas in front of you; the price to pay is having to deal with many ups and downs and sometimes the climbs are many and steep. Not to discourage anyone, but there is a work of research, understanding, and getting to a result is often very difficult.
Many college graduates believe that once they enter the job market, they can immediately start building mathematical models. You have to be smart and use powerful tools. The bulk of the work is going into each data. I repeat that the Data Analyst is an interesting job, sometimes dry, but certainly demanding.
What is the greatest satisfaction that Data Analyst can have?
When you see that the service you created gives a utility. They often ask you for information with very tight deadlines, complex information, rather than basic information. You try, you make mistakes, and you try to provide them. Sometimes it takes a little longer, sometimes less. Knowing or seeing that some hypotheses you have made are then supported by the data and seeing on the other side that the activity you have done is useful and has brought value, is satisfying.
Speaking of my daily life, I am now collaborating with the commercial sector and I have discovered that many are using a report that I had made. Two people thanked me and told me that my reporting work helped them a lot in the business.
With which digital professionals does the Data Analyst interact?
In my personal experience, but also looking at that of my colleagues, I have seen that Data Analysts often interface with SEOs or with the figures who create content. MailUp, for example, creates and offers reports on the use of email marketing, this is because it can count on a large database and many customers who can represent the use of digital.
Or I saw some of my colleagues interacting with the product team for the evolution of the same, otherwise with the UI and UX designer business unit for the use and evolution of the platform, to see what can be improved, what new features can be inserted, to reach the marketing division to be of support when developing campaigns. With marketing, the objectives can be the measurement of ROI, the generation of targets, and the comparison of the “performances” of the various campaigns.
The company always needs to track information and the Data Analyst also has the task of verifying its correctness. This is a further facet of the job that becomes interesting because it allows you to understand business processes. In conclusion, through the number, the Data Analyst tries to obtain qualitative information. For this reason, he must know both the processes and the company’s qualitative needs, otherwise, it becomes impossible for him to extract, process, and measure phenomena through data. Only by knowing the purchasing process and the recorded phenomenon does the study of the data take on meaning. This is an important and also one of the hardest parts of the job.
What would your ideal alter ego be?
An alter-ego with whom to have close collaboration, a real partner to understand clearly from him what data he is looking for, what information he feels the need, and what question he is interested in. Let’s go back to what I said at the beginning, the Data Analyst is at the service of other company divisions, he is not a figure that can exist alone. He always needs a question to answer that leads him to discover possible new insights. So a competent person, curious and who has questions to answer.
Is this a job that can also be done as a freelancer?
I would like to say yes, it is possible. Surely it is necessary to have a dialogue with the entrepreneur or in any case with the other figures on the customer side because, as already repeated, without a need it is a profession that does not exist. If it is possible to have this dialogue, to understand these needs, and to have a network of customers then yes, it is certainly possible.
If it is possible to establish this dialogue then it is possible to be able to have a certain clientele, even if the world of small and medium-sized enterprises is still to be discovered. Looking at my working past, it may happen that in the end with the data available, it is often “only” possible to demonstrate what people, entrepreneurs already know: you are providing them with the numerical rationale they did not have before. From that number it is then possible, data permitting, to undertake a more in-depth cognitive path, to face problems.
So your profession is only suitable for companies starting to have a certain size?
This is quite a challenge. I would tell you no. It doesn’t have to be a corporate one; that determines the amount of data, the technology that can be used, and the costs. Indeed, the desire that I have always had – and that I don’t know if it will be able to see an outlet – is to be able to be at the service of the small and medium-sized enterprises that make up the entrepreneurial fabric.
As a Data Analyst, I’m fascinated by the possibility that even a small business owner can benefit from data analysis for his business. I know of small business owners who have some analysts on their team and maybe don’t invest in marketing. In this case, they are in support of management control rather than the sales sector, while keeping marketing more unguarded. I think that it is useful for anyone to have a figure who in some way – also taking into account the path towards a digitized world – “grinds” the numbers to understand where he is going and where he can go.
Could an outsourced figure make a difference for the PMI?
Yes, then I don’t know what types of business they could fall into. To be clear, I did some experiments, for friends or relatives. My uncle sells clothes and at the time my father built him a database with customer and sales data. It’s a much smaller size, but it could fit into my current activities. A small tool that, however, gave contribution to the business of my uncle, a small businessman, with a small clothing store.
How much does a Data Analyst earn on average?
I checked the values of salaries and looking at my salary and that of my friends with the same degree, I would say that we are above average. The difference can be made, as I mentioned at the beginning, by the union of the Data Analyst profession with that of the Scientist.
In this case, the Data Analyst tends to support the business, describing the events, without entering the field of probable and possible study. Even just looking at the job requests on LinkedIn, the job offers for Data Analysts and Data Scientists have a certain difference in salary, and pay, not trivial.
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Conclusions and Career Advice
At this point, the importance of the Data Analyst figure for companies should be clear, in particular, to solve problems and offer advantageous solutions and opportunities. Through adequate training, anyone with the right passion and resourcefulness can become a data analyst and launch into this sector.
And you can do it too simply by requesting Free Career Coaching with a digital marketing expert who will guide you toward the path that best suits your needs.
Becoming an expert in the field of data analysis will allow you to take full advantage of all the information that is available to you where, through the collection and study of data, you will be able to develop strategies that will allow you to make decisions to create ambitious business models and revolutionaries for business growth.
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