Is python useful for Business Analysts?

Business Analysts are responsible for gathering, analyzing, and documenting the business requirements. There are circumstances where Business Analysts have to interact with data to study requirements. Python is a versatile programming language that can be used for a variety of purposes, including data analysis.

So is python useful for Business Analysts? Yes! Python is useful to Business Analysts if they are working on a project that requires advanced data interaction and manipulation, such as segregating, clustering, and categorizing data. However, it is not required to be knowledgeable in python to become a Business Analyst.

There is a certain misconception about Business Analysts and their roles and responsibility that often leads to confusion about what is useful or required to be a Business Analyst.

Let’s take a more detailed look at where a BUsiness Analyst might require python and if it is necessary to learn python for the role.

Business Analysis and Data

The fundamental role of the Business Analyst is to gather, analyze, and document business requirements. While the BA role extends beyond just requirements gathering, this is where it starts.

Business Analysts are involved in all types of projects across different industries. Every IT or digital transformation project has its peculiarity and varies greatly in its implementation and requirements.

From process improvements to platform migration, web development, software development, and cloud implementation projects.

These projects require different skills, and some skills are more desirable than others which makes the Business Analyst career versatile and interesting.

Data manipulation is one of those skills that are required in some projects and less important in others. To be clear, the ability to interact, interpret, and makes sense of data is an essential skill for Business Analysts.

However, the advanced ability to manipulate data is not essential but might be required from employers on certain projects.

What is python

Python is a programming language that is commonly used to create websites and applications, automate operations, and perform data analysis.

Python is a general-purpose programming language, which means it can be used to develop a wide range of applications and isn’t tailored to any particular problem.

Because of its versatility and beginner-friendliness, it has become one of the most widely used programming languages today.

It is currently the top programming language in the world today in TIOBE and PYPL Index. TIOBE ratings are calculated by counting hits of the most popular search engine, while the PYPL Popularity of Programming Language Index is created by analyzing how often language tutorials are searched on Google.

Python has become a data science standard, allowing data analysts and other professionals to perform complex statistical computations, produce data visualizations, design machine learning algorithms, handle and analyze data, and perform other data-related tasks using the language.

Python can create a variety of data visualizations, including line and bar graphs, pie charts, histograms, and three-dimensional plots.

Python programming language is essential for Data Analysts, Data Scientists, Business Intelligence Analysts, and Business Analytics.

Advantages of Python for Business Analysts 

There are a few advantages of using python as a Business Analyst, such as –

#1 Data Manipulations and Visualization

Python can help Business analysts working on a data-heavy project identify data, collect the data, clean the data, prepare the data for analysis, analyze the data, and finally interpret the results of the analysis.

Most organizations will have a dedicated data analyst for this, but some won’t!

Furthermore, Python can be used to make 3D plots, histograms, charts, and graphs.

It also gives you advanced modeling that can help you with price forecasting with the help of econometrical models, segmentation of clustered algorithms, classification of products, and estimating product price elasticity. Yes, pretty technical stuff!  

#2 Enhanced productivity 

Python is versatile and can be used for everyday tasks to make work more efficient.

Here are just a few of the tasks a Business Analyst could automate with Python:

  • Monitor and track an inventory
  • Send text reminder notifications
  • Update a data list
  • Rename a large batch of files
  • Convert text files to spreadsheets
  • Fill out online forms automatically.

#3. Additional Skill & Market value

As its a popular programming language, your knowledge of Python certainly gives you an edge in the job marketplace.

It’s important to emphasize this skill will be more relevant to a Busines ANalyst assigned to a project that involves manipulating and segregating data.

As a Business Analyst with advanced data analysis skills, your market value is slightly more provided you have the projects and experience to back your skills.

You are more valuable to an organization that would rather have a single Business Analyst who can gather requirements as well as interact with data to get insights and predict outcomes.

Thus, you can request higher compensation. Just be careful not to be overworked!

The roles you can apply for also increase, and you are able to perform the different functions and requirements for the different roles.

Disadvantages to Business Analysts

There are not any major disadvantages of acquiring the knowledge of Python aside from the time and resources required to learn and master the skill.

However, if this is a skill you would like to acquire because of the stated advantage above, then the time required is not a disadvantage. You could still work as a Business Analyst.

Other technical disadvantages include speed to execute code, not memory efficiency, weak mobile computing, and runtime errors. However, these are not relevant to Business Analysts.

Should a Business Analyst learn Python?

As stated above, python is a useful programming language for data manipulation and interpretation.

Beyond data analysis, there are other uses for python, including

  • web development
  • Testing and prototyping software
  • Machine learning
  • Scripting

As a business analyst, if you have a plan to transition into Data analyst roles or if you have a preference for working on data-heavy projects, then yes, you should learn python, as this will certainly give you an edge in the job marketplace.

If you don’t have any of those plans, then you don’t have to learn Python to be a Business Analyst.

Final thoughts

As a Business Analyst, there is nothing stopping you from acquiring python skills to be a specialist business analyst with advanced proficiency in data manipulation and analysis using python.

Is this skill going to be useful in your BA career? Perhaps if you are always working on projects that require that level of data manipulation, then yes.

However, it should be made very clear that you don’t need python knowledge to be a business analyst, and Business Analysis should not be confused with Business Analytics.

Frequently Asked Questions

Should business analyst know Python?

Business Analysts should know python if they have a preference for working on projects that require advanced data analysis and manipulation skills. Also, if you plan to transition into Data Analysis or Business Data Analysis, python knowledge is an advantage.

What is the use of Python in business analytics?

Python can be used to describe and classify large sets. They perform exploratory data analysis, which includes profiling the data, visualizing the results, and making observations to help shape the study’s future phases. Python may be used to manage data, automate procedures, and produce visualizations.

Is coding necessary for a business analyst?

Business Analysts are responsible for gathering, analyzing, and documenting business requirements. Thus, coding is not necessary for Business Analysts.

Is Python required for business analyst?

Python is not required to be a Business Analyst. However, it is useful for data analysis, manipulation, interpretation, and visualization of data.

Patrick is passionate about supporting other professionals to find success in their chosen career paths. So far, he has successfully navigated four career transitions and is currently a Product Manager Consultant helping businesses build products their customers love.