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Disparity among Business Analyst and Data Analyst

Business Analyst and Data Analyst both work with data. The difference is what they do it. Business analyst gathers data to make strategic business decision. And Data analyst gather data, manipulate it, identify useful information from it and transform their findings into a new project. Their end goal is analyzing data.

People in either role need to have a good problem-solving skill, an analytical mind (to analyze the data) and ability to work towards a big picture. But technics and role is totally different, it is equally important to understand how they differ.

  • Business Analyst gathers data , and use that data to identify problem and solutions, They do not perform a deep technical analysis of the data. They operate at a conceptual level, communicating with stake holders, defining strategy and are concern with a business implication of data. On the other hand, Data Analyst spend the majority of their time to gathering raw data from different sources, cleaning and transforming it and applying a techniques to make out useful information and develop output.
  • Business Analyst has industry experience in areas such as e-commerce, banking, manufacturing or healthcare. People in this role require less technical skill in comparison of Data analyst, although they need a knowledge in Databases, networks and common programming languages.
  • Business Analyst must be proficient in requirement gathering, elicitation technique whereas Data Analyst need strong business intelligence and data mining skills, also proficiency with in-demand technologies like Artificial intelligence and machine learning.
  • Business analyst comes from backgrounds in management, business, related fields. On the other hand Data analyst comes from math or information Technology background. Data analyst requires an understanding of complex statistics, algorithms and database.

The requirement of business Analyst includes:

  • Expertise with requirement gathering.
  • Strong communication skills.
  • Mathematical mindset and expert analytic capabilities.
  • Strong in Microsoft office, MS PowerPoint, MS Visio, Prototyping technique.
  • Project management experience.

The requirement of Data Analyst includes:

  • A good knowledge in data mining.
  • Good in technical skills.
  • Knowledge in SQL, Python and in-demand languages.
  • Good with emerging technologies, data framework and machine learning.

How to choose Between a career as a Data analyst and Business analyst:

Which career path is the right one for you: Data analyst or Business Analyst? To determine that, you will need to consider three factors:

  • Your educational and professional background.
  • Your interests
  • Your desired career path

 

Business analyst v/s Data analyst

 

  Business Analyst Data analyst
Goals Focuses on identifying trends in the organization that can be optimized to improve overall business planning and performance.

 

A benefit comes from recognizing patterns in dataset and making accurate prediction based events.
Data Data sources are defined in advance based on project goals. Analysis is more ad hoc with data sources
Approach Involves defining the goals and requirements for projects.

 

More retrospective and descriptive.

More predictive and prescriptive.

 

 

Team Members BA, Senior BA, Stakeholders, Project manager, Technical team, Quality assurance. Data analyst, line of business manager.
Tools MS Excel, MS Visio, Prototyping Technique Artificial intelligence, Machine learning

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