Similarities and differences between a data analyst and a business analyst

Introduction 

It is said that data analytics and business analytics are two sides of the same coin. However, there is a stark difference between the two terms as well as a high degree of correlation. While data analytics deals with processing and analysis of data for the purpose of deriving insights from it, business analytics is concerned about harnessing the power of data for business purposes. This means that the prime difference between business analytics and data analytics is related to their utility for a particular purpose. In this article, we highlight the differences between the two terms as well as their degree of convergence. 

 

Methodology and goals

Both business analytics and data analytics share a common methodology but their goals are different. Both business analytics and data analytics source information from different data sets, process it and analyze it from a scientific perspective. While the goal of data analytics is to condense data sets so that meaningful information can be derived from it, the goal of business analytics is completely different. Business analytics uses data as a raw material to make company decisions that are supported by data. In this way, we conclude that business analytics makes use of predictive analytics rather than data analytics in a simplified format.

 

Similarities and differences between a data analyst and a business analyst 

It is the mode of working or the modus operandi that accounts for the similarities between a data analyst and a business analyst.

For instance, a data analyst works on the population of a city and classifies it on the basis of age and employment. For this purpose, a data analyst first collects the census data about the entire population.

Secondly, he collects data about the formal and informal mode of employment. After authenticating this data, he classifies the people on the basis of their age or employment and establishes correlation between the two.

Finally, he communicates the findings in the form of pie charts or other visualization techniques.

Let us assume that a business analyst also needs to analyze the population of a particular place on the basis of age and employment levels. However, the goal of the business analyst is to study the relevance of a particular product to a specific group of population.

Before being formally introduced into the market, a pilot study seems to be the best option for a business analyst to foresee the commercial potential of the product.

Although the working methodology of a business analyst may be similar to a data analyst, the deviation begins at the stage of data processing on the basis of certain parameters for a certain purpose.

That said, the goals of a data analyst and a business analyst are completely different. We conclude that a business analyst is a data analyst with a lot of market experience and tilt towards business dynamics.

 

The skill set of a business analyst and a data analyst 

The skill set of a data analyst is very technical in nature. He must possess skills related to data mining, data processing and data analytics. In addition to this, he must also be proficient in subjects like statistics, mathematics and probability. He must have good knowledge of computer science, machine learning and natural language processing. He must have very good programming skills.

When we look at the skill set of a business analyst, we find that the two most important skills that he should possess include critical thinking and interpersonal skills. He should have good communication skills as well. While it is advantageous to have some programming skills, it is not what counts as a primary skill for a business analyst. 

 

Which career to choose among business analytics and data analytics?

There is not a binary answer to this question. Both fields of data analytics and business analytics have their own scope and importance. Hence, it is highly advisable to choose a field depending upon one’s interest and experience. If one is highly inclined towards mining of various data sets and deriving insights out of them, a career as a data analyst seems to be the perfect choice. Similarly, if one is inclined towards data analytics and visualization from a business perspective, a career as a business analyst should be the best fit.

 

Conclusion 

We may expect the lines of demarcation between data analytics and business analytics to fade away in the coming times as interdisciplinarity makes its way to the middle. 

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