Skills Needed for a Business Analysis Professional

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What is the most important skill you need to be successful in mastering analytics? I've seen this question floating everywhere: our discussion forum, social networks and even on chat platforms. Then, Is there such an absorbing ability?

The answer, as you may have already guessed, lies in the combination of various skills. Business analytics is a broad field that encompasses a number of skills we need to be successful.. There is no one-size-fits-all approach. But this is the good news: there are some key skills you can acquire to ensure you become a good business analytics professional.


Gone are the days when people were valued just for having a degree. Business analytics domain doesn't work like this!! The market pan-industry has evolved from a title-focused industry to a skills-based industry. Yes indeed, No one is asking you not to go to universities or to drop out! But don't just rely on a degree if you want to become an analytics professional..

Education grants you a job, but skills increase your growth prospects. In this article, we are going to explore the most important skills required by a Business Analytics professional. Please note that this list is not exhaustive, but it covers the absolute basic skills you must acquire.

In case you are interested in starting your journey in Business Analytics, check out the following free resources:

Table of Contents

  1. Difference between a business analyst and a business analysis professional
  2. Technical skills in business analysis
    1. Statistic and probability
    2. Data recovery
    3. Statistical tools
    4. Statistical programming
    5. Display
  3. Soft skills for business analysis
    1. Communication
    2. Structured thinking / critical
    3. Problem resolution
    4. Curiosity

Difference between a business analyst and a business analysis professional

I have often seen in the industry how people use the 2 above terms in a similar context. From top industry leaders and recruiters to the common man, everyone uses the term incorrectly. Let's clarify the difference.

A Business analyst it's more on the managerial side. His focus is more on the analysis and efficient development of the activities that make up a business. This includes interdepartmental communication, policy formulation, etc.

For instance, the business analyst acts as the gap between the customer and the sales department and ensures that all communications go smoothly the way they want.

A Business analytics professional focuses more on statistics, data, reporting and data logging. They also aim to improve various functions in a company, but the difference is that they analyze numbers to do it.

In the following sections, let's read about the key skills a Business Analytics professional should have.

Technical skills for business analysis roles

Let's look at the technical and theoretical skills necessary to become a good business analytics professional.

A) Probability and statistics


Statistics and probability help you understand the numbers, answer some of the relevant hypotheses and make better predictions. For instance-

  1. Average units sold during the sales season?
  2. How much do the units sold vary daily?
  3. Is the percentage of leads qualified but not ready to buy??
  4. The average number of calls required for a successful conversion.
  5. Percentage of customers who buy our products with respect to our market

What's more, using statistical methods such as regression and time series, one can make relevant predictions about similar expected future sales, the probability of achieving the stated objectives, etc.

B) Data recovery

What will you do with all the knowledge and skills if you don't know how to retrieve the data from the database management system (DBMS) of a company in which you will apply all your analytical skills? That's what data recovery is for. Data recovery is the identification and extraction of the necessary data from the database using a command line.

But, How do we extract the required data from a large amount of data based on the stated goal? This is precisely where SQL come to play. SQL is a programming language specifically designed to work with large databases, especially relational databases.


There are many database management systems available in the market like Oracle, MongoDB, SQLite. But the most famous one used by a lot of big-name organizations and aspiring candidates is MySQL.. It is the highest rated open source DBMS that is famous for its maturity and reliability.

You can check the following course: Structured query language (SQL) for data science

C) Statistical tools

Once you have the data, you need to know at least one statistical tool, where you can import that data and perform analysis. Some of the statistical software include: SPSS, SAS, Sage, Mathematica, etc.

Nowadays, the highlight that anyone can learn from anywhere in Microsoft Excel. MS Excel is a spreadsheet that helps to analyze and plot the data. It also performs a large number of complex mathematical and statistical functions. All you have to do is write the formula and select the data range for which you have to calculate the parameter.


In case you are interested, see this course: Microsoft Excel: from beginner to advanced-2.0

D) Statistical programming languages

Knowledge in a statistical language is a recent demand in the industry. And the most used languages ​​are Python and R. The reason for this is the volume of data that is currently generated, you need tools that can easily manage such volumes of data. There is 2 main benefits of statistical programs.


First, facilitate data transformation and you can easily create new variables using existing ones or perform mathematical transformations based on the distribution of a variable.

Secondly, these languages ​​are rich in libraries that help to create predictive models with ease. For instance, a single library, sklearn, in python can help you create most models with ease. The combination of these two makes a statistical language better for handling large and complex data..

In case you are interested, see this course: Introduction to Python

E) Display

Data is visualized in all industries of the 21st century. It serves as a bridge between what business analytics professionals do and what the customer / stakeholder needs to know. With real-time visualization coming into the game, The entire display spectrum has been raised to another level.

An aspiring candidate must know the importance of visualization and a clear understanding of which graph or chart will be used for a particular set of data..

Nowadays, the most prominent visualization tool on the market includes: PowerBI, Table y Qlik Sense.

power-bi-vector-logo-6718367 tableau-logo-no-border198x150-7749911 qlik-sense-logo-2-2307873

You can check out our course on Tableau here.

Soft skills required for business analysis roles

There are a number of qualitative personalities and skills that make a technically efficient business analysis candidate well-rounded.. The following are some of the outstanding soft skills that a business analytics professional should have.

1. Communication skills

In the era where all activities can be automated, it is the soft skills that will help you differentiate yourself and the most important of all is communication. A candidate in this industry must be able to convey their analysis and thoughts in the simplest way possible without losing complex details..


What's more, Another important aspect of communication that you need to master is your listening skills. You need to understand the needs of the departments on whose basis you will query the data, will analyze and visualize them.

2. Structured and critical thinking

A thinker always brings a new perspective and angle to the work they do. Critical thinking would not only help you interpret the implications of the analyzed data, it will also help you understand what data needs to be collected first to analyze.

What is structured thinking and how can it help you?

It will also help you decide what type of analysis will be performed and what type of visuals will be used to communicate the analysis more effectively..

In case you are interested, see this course:Structured thinking and communication for data science professionals

3. Curiosity

Curiosity is the path to critical thinking. Asking the right questions at the right time will only help you improve your understanding and thinking.. What's more, leads to deep and rational thinking and helps to discover more creative solutions to the current problem.

Many organizations consider curiosity a necessary skill, as it leads to fewer errors when making decisions. What's more, leads to positive thinking and open communication within the team.


4. Problem resolution

Problem solving in the business analytics industry requires the person to logically apply a combination of thoughts, processes and actions to effectively and correctly achieve the final objective you want.

What's more, a good problem solver assumes less and does more research to understand what you are dealing with and how to move on. Look for a possible solution by analyzing what is happening in the industry, what the potential future looks like and what you can do to address it.


5, apprentice for life

The more you learn, more grows. None of us are born with analytical skills and many of these skills are learned as we go.. Therefore, one must have the will to constantly learn and improve one's skills.


Final notes

To complete, in this article, we understood the skills required in the business analytics industry. What's more, We analyze the history of the business analysis profession and also explain, in summary, the difference between a business analyst and a business analysis professional.

In case you want to pursue a career as a Business Analytics Professional, check our program:

What's more, you can refer to the following article:

What skills do you think are best for aspiring business analytics? Let us know in the comments below!.

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