Business Analytics and Data Analytics — What’s the difference?
Introduction
Analytics has become the core driving engine for business development & transforming how organizations used to make decisions. All of the credit goes to data-driven insights and specifically Big Data. Whether it is a large or a small organization, the streamlining of data coming from a plethora of sources is helping different companies leverage these data to boost sales, make strategic decisions, increase reach, help in better campaigning, etc. To extract the maximum benefit of data, both large & small organizations should use business analytics and data analytics together.
But there is mayhem among people between these two terms. While some people often use these two terms interchangeably, others feel confused about which one to use and when. If you are experiencing such a dilemma, then this article is for you. In this article, we will discuss what business analytics and data analytics is & how they differ from one another.
What is Business Analytics?
Business analytics is a data management process and a subset of business intelligence that leverages statistical methods and technologies to render business insight from past data. According to Globe News Wire, the business analytics market will grow by 18.88 billion USD during 2021–2025. According to their prediction, this will bring a CAGR of almost 16 percent during the forecast period. Business analytics enable business leaders and decision-makers to take better and more strategic decisions for the growth of the business.
According to Glassdoor, the average salary of a business analyst is Rs. 7,89,000 per year. The business analytics team performs operations like data aggregation, data mining, predictive analysis, sequence identification, text mining, and statistical analysis from the business perspective.
We can categorize business analytics into two categories:
· Descriptive analytics: Here the business analysts work with historical data to decide how a product or business item will respond as per the set of metrics.
· Predictive analytics: Here the business analysts employ historical data to determine the future outcome of any product or business item.
What is Data analytics?
Data analytics is a branch of data science that deals with the process of analyzing raw data from various sources to find trends and make insightful findings from the data. Data analytics require a lot of specialized tools and applications that can either automate or ease the process of understanding data-driven acuities.
According to Glassdoor, the average salary of a data analyst is Rs. 6,00,000 per year. Today almost every company is leveraging data analytics to understand the pattern and direction of the business & operations and make informed decisions from granular data. That’s where companies hire data science professionals and data scientists with proficiency in statistics and mathematics to do such work.
According to PRNewswire, the big data analytics market will grow by 145.24 billion USD during 2021–2025. According to their prediction, this will bring a CAGR of almost 12 percent during this forecast period.
Business Analytics vs. Data Analytics –
Although business analytics and data analytics work closely with data, the difference lies in various factors like what they do for the business, what they do with the data, what skills are necessary for data analysis and business analysis, etc. In this section, we will see the differentiating factors in the form of points.
Skills required for Business Analytics and Data Analytics –
Business Analyst –
A Business analyst has to be proficient in hard skills like:
· Statistics
· MS. Excel
· SQL
· Data mining
· BI and BI tools
· Data visualization tools
A Business analyst has to be proficient in soft skills like:
· Good communicator
· Problem solver
· Critical thinker
Data Analyst –
A Data analyst has to be proficient in hard skills like:
· Python or R
· Statistical and Mathematical skills
· Data visualization libraries and tools
· Web-based data analytics tools
A Data analyst has to be proficient in soft skills like:
· Curious mind
· Good communicator
· Problem solver
· Critical thinker
Conclusion –
Despite the differences between data analysts & business analysts, both these careers are promising and have great demand in various sectors across industries. There are times when both business analysts and data analysts have to work closely to provide significant insight from granular data. If you are looking for any of these profiles, this is high time.
