How to become a Data Analyst?

As data becomes increasingly important for businesses, the demand for skilled data analysts has skyrocketed in recent years. If you're interested in becoming a data analyst and want to know the steps to get there, read on for a comprehensive guide on how to start your journey.

Human brains (but I am quite sure not only ours) perform complicated analyses daily. Of course, the level of complexity varies between analysing which cheese is the cheapest in our favourite grocery store and choosing which parameter would be the best to put in the algorithm equation that would help to start our spacecraft into space. Nevertheless, each of us have an element of analytical thinking which helps us perform and understand many things in our lives.

In IT environment such analytical thinking is mostly applied too data and this is referred as Data Analysis (obviously). And people who work in this field are Data Analysts (yes, you are right, you get paid for your one of the most primary brain function). Here, I would like to talk about who is Data Analytic, but before that let’s briefly explain what Data Analysis is all about.

Data analysis consists of processes such as: inspecting, cleansing, transforming and modelling data. The aim of those actions it to discover useful information, make reasonable conclusions and support making right decisions. There are many fields of Data Analysis which differ in approach or performance technique and are used in different business or science business. Nowadays, data analysis makes businesses operate more effectively, very often helps to reduce costs of solution and makes decisions science-based.

As definition of data analysis was shortly, but briefly explained (I hope so) let’s dive into who Data Analyst is. Simple put, data analyst is a person who perform tasks that will lead to complete actions in scope of data analysis. Those include: identifying, collecting, cleaning, analysing and interpreting data. To be more specific this role assumes you will:

• apply tools and techniques for data analysis and data visualisation (including the use of business information tools)
• identify, collect and migrate data to and from a range of systems
• manage, clean, abstract and aggregate data alongside a range of analytical studies on that data
• manipulate and link different data sets
• summarise and present data and conclusions in the most appropriate format for users

Of course to do all above, the set of skills every data analysts should have exists and this:

• Applying analytical techniques to present a solution.
• Great communication is a must have as you will have to share insights of your work and you knowledge with colleagues, leaders and stakeholder.
• Data management, you need to study and get used to a different types of data
• Data modelling, cleansing and enrichment. You can understand conceptual, logical and physical data modelling. You can develop knowledge of data cleansing and standardisation.
• You can conduct data quality assurance, validation and linkage.
• Visualisation as beautiful and clear graphs are better to interpret and understand.
• Be good in mathematics and computer science. Thinking logically and having a common knowledge of IT field in data analysis is like being able to breath, it is just necessary.
• Creative thinking brings fine and simple solutions to complex issues.
• Project management. Advancing in to the next career ladder as a data analyst will lead you eventually to be responsible for the whole project.
• Statistics. You can demonstrate knowledge of statistical methodologies and data analysis techniques.

How to become a Data Analyst?

First of all get a foundational education. At least bachelor degree in any of those: computer science, mathematics, statistics, economics and other related. ‘But why?’ you could ask, specifically in times when employers do not expect a science degree as much as they used to, well studies teach us self-motivation, looking for answers, being curious and on top off all that it helps to get strong fundaments of mathematics, statistics and computer science (at least from my experience).

Second step is to become good (fluent in the best case) with technical tools. Those cover: any programming language (I’d recommend Python in the first place, then R), databases (SQL), visualizations (Tableu, PowerBI), services (Git), cloud solutions (AWS, Snowflake). Start early with those, get theoretical knowledge, and use it in practice by doing projects with real data (here also being on studies helps) or coding. You can use  GitHub to place your projects and create your portfolio. Remember, you do not need to be a master with those tools but just be comfortable with all of that.

Third, start early and be patient. Start early means you should do/create projects regarding real data as soon as possible. Get used to the whole commercial technology, learn different types of data and start looking for any internship that refers to Data Analyst role. Do not wait until someone will occasionally give you some solutions to solve, try to look for you own (I would recommend GitHub, Data Camp or Udemy to search for any projects ideas/courses). Being patient means that you will not give up after a simple failure. Remember, learning path is a long one, it is not linear change, keep it in mind that eventually you will not progress as you would like to. Just keep studying and be positive. Also being patient is necessary while looking for your first job/internship as Data Analyst. Send as many resumes as possible to every employer you could find and just wait. Trust me, someone will answer. While waiting for the response just keep learning.

All above is, more or less, formally in terms of a definition who data analyst is. Here, I would like to throw in one’s two cents, and talk about main topic from my subjective perspective as a data analyst. It is true that sometimes you do not need any degree, if you are good enough and completed good courses, to get a decent first job, but my opinion is that studies helps a lot to achieve this. And yes, unfortunately I would recommend finishing one of the mentioned field of study. I would also want to repeat myself, please start as soon as possible, it applies to learning and looking for a job, the faster the better.

Being Data Analyst is not only about analysing/modelling/managing data, but (I assume it is even more important eventually) it is also about communicating with people. You will have to spend a lot of time on various meetings. Very often you will have report your work and send it to other people. So you need good communication skills. And do not forget about asking a lot of questions. It feels like being a little bit snippy person, but trust me it is worth.

The last thing is that being Data Analyst requires of you delving into other areas of data related projects. You will probably need knowledge from data engineering/data science field because you will cooperate with people from different areas. Thus, Data Analyst must understand more than data analysis things. Do not worry though, the knowledge will come if u fulfil a conditions mentioned in a previous sections.

Author: Damian Kokot

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