Business Analytics and Data Analytics – What’s the difference

Business Analytics

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 streamline of data coming from a plethora of sources is helping different companies leverage these data to boost sales, make strategic decisions, increase reach, helps in better campaigning, etc. To extract the maximum benefit of data, both large & small organizations should use Wicked Reports for 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 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, business analysts work with historical data to decide how a product or business item will respond according to the set of metrics.
  • Predictive analytics: Here, 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 analyzing raw data from various sources to find trends and make insightful findings from the data, by solving projects on ProjectPro Data Science projects you can gain and learn everything about Data science and Data analytics. 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 with proficiency in statistics and mathematics to do this. 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.

Business Analytics Data Analytics
It is the study and analysis of business data through statistical analysis and models. It is the study and analysis of complex raw data through tools and algorithms.
Business analysts help the organization find business insight through statistical techniques and BI tools. Data analysts help the organization identify patterns using data analytic tools.
It deals with much simpler data as compared to data analytics. It deals with complex data as compared to business analytics.
It benefits in the continuous improvement of technology, processes, corporate operations, and business approaches. It aids in recognizing filtered datasets that can help in accurate predictions based on events.
It requires more statistical models, business concepts, previous records, and statistical analysis. It requires more logic, algorithms, and code to identify the conventions and patterns.
The business analysis deals with past data & concentrates more on comprehending the present situation of the business. It pulls out hidden patterns from the data to help the organization predict the end-user demands & forthcoming requirements for the company.
All the data sources associated with the business analysis remain defined in advance. Mostly the data sources remain static or fixed. The data sources do not remain specific in advance in data analysis. The data sources are moistly dynamic and ad-hoc data sources.
It primarily deals with structured data that gets taken from the business model. It mainly deals with two to three types of data: structured, semi-structured, and unstructured.
It deals with specific business goals and requirements. It deals with particular questions and discovering insights.
The investment cost is low compared to data analytics. The investment cost is high compared to business analytics.
It helps in making cognitive analysis tools and visuals for business development. It helps in enhancing and making precise machine learning models.
Its results are specific and based on past data for the development of business. Its results are generic and based on patterns to analyze the future prospects.


Business Analytics vs Data Analytics – Skills Required

 Business Analyst –

Technical Skills Needed for a Business Analyst

  • Statistics
  • Excel
  • SQL
  • Data mining
  • BI and BI tools
  • Data visualization tools

Soft Skills for a Business Analyst –

  • Good communicator
  • Problem solver
  • Critical thinker

Data Analyst –

 Technical Skills Needed for a Data Analyst

  • Python or R
  • Statistical and Mathematical skills
  • Data visualization libraries and tools
  • Web-based data analytics tools

Soft Skills Needed for a Data Analyst

  • Curious mind
  • Good communicator
  • Problem solver
  • Critical thinker

Despite the differences between data analysts & business analysts, both these careers are promising and have a great demand in across industries. There are times when both business analyst and data analyst has to work closely to provide significant insight from granular data. If you are looking for any of these profiles, this is high time.

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