If you love working with data, you may find yourself at a crossroads when it comes to choosing a professional career between a data analyst and a business analyst. Just how do you choose between becoming a business analyst or data analyst?
The good news is that both roles let you capitalize on your love for data. Then, what is the difference between a data analyst and a business analyst? Data business analysts are all about analyzing data sets and uncovering the trends to use in making an informed decision in organizations.
On the other hand, business analyst professionals are critical thinkers, problem solvers, and excellent communicators. These professionals have a detailed knowledge of their organization’s objectives and processes so they can evaluate performance, identify inadequacies, and advise and implement solutions.
If your question is, can a data analyst become a business analyst? Well, a data analyst can, over time, switch to the role of a business analyst. The same is true in reverse.
Let us now look at the difference in roles of a data analyst and a business analyst.
Business analytics vs. data analytics: An overview
Both business analytics and data analytics involve working with and manipulating data, extracting insights from data, and using that information to enhance business performance. So, what are the fundamental differences between these two functions?
Business analytics focuses on the larger business implications of data and the actions that should result from them, such as whether a company should develop a new product line or prioritize one project over another.
The term business analytics refers to a combination of skills, tools, and applications that allows businesses to measure and improve the effectiveness of core business functions such as marketing, customer service, sales, or IT.
Data analytics involves combing through massive datasets to reveal patterns and trends, draw conclusions about hypotheses, and support business decisions with data-based insights.
Data analysis attempts to answer questions such as, “What is the influence of geography or seasonal factors on customer preferences?” or “What is the likelihood a customer will defect to a competitor?”.
The practice of data analytics encompasses many diverse techniques and approaches and is also frequently referred to as data science, data mining, data modeling, or big data analytics.
To understand this with visual cues, check out the video below.
Business analytics vs. data analytics: A comparison
Most people agree that business and data analytics share the same end goal of applying technology and data to improve business performance.
In a data-driven world where the volume of information available to organizations continues to grow exponentially, the two functions can even work in tandem to maximize efficiency, reveal useful insights, and help businesses succeed.
This side-by-side comparison should help clear up some of the confusion between business and data analytics.
Business analyst vs. data analyst: A comparison of roles
Business analysts are experienced professionals who assist in improving the existing business processes by understanding the key issues and improving the efficacy through their analysis and critical thinking capabilities.
When an organization is required to resolve a problem that is pertaining to current or future aspects of the company, the business analysts are responsible to take matters into hand and provide a necessary solution to this. Their typical role in the organization is:
- Working with the clients to understand the problem and defining the problem statement.
- Analyzing the current and future business needs by extracting the current data
- Understanding requirements of the company and the client projects
- Communicating the client’s requirements to the development team
- Developing and Managing the Client Projects
- Working closely with the Client and the Development team to help in escalating issues wherever necessary and ultimately developing useful solutions for the client
- Making important business decisions for the company based on their analysis
- Testing the developed use case before handing the solutions to the client
- Reviewing current trends and implementing various tactics to improve and change the current trends that may seem outdated for the system
Data analysts normally don’t work with clients directly, their primary role is to work with the data, explore the features of data, create actionable insights and reports for better understanding.
They use techniques from mathematics, statistics, and computer programming to draw further conclusions from data to describe and improve their existing business performance. Their typical role in the company is to:
- Extract, Collect and Interpret data
- Deeply analyze the results
- Creating actionable insights and reports to present it to the company
- Identifying trends that are present in the data sets to come to the conclusion
- Understanding business needs and creating use cases and reports based on the requirements of the company
- They work closely with the management team to prioritize the current business needs
- Ultimately they are also required to define the ways to improve the current business processed based on their findings
Aside from technical and role-specific skills, business and data analysts each need some additional abilities to be successful.
A business analyst needs to be able to:
- Take a holistic view of a business problem or challenge
- Work with individuals across the organization to get the information necessary to drive change
- Develop clear, understandable business and project plans, reports, and analyses
- Engage and communicate with stakeholders at all levels of the organization
- Present recommendations clearly and persuasively for a range of audiences
A data analyst needs to be able to:
- Translate data into meaningful business insights
- Work well independently
- Identify relevant data sets and add them on the fly
- Report results in a clear and meaningful way
- Define new data collection and analysis processes as needed
From the newest startups to established global enterprises, every organization needs to leverage data for innovation and business growth.
The practices of data analytics and business analytics share a common goal of optimizing data to improve efficiency and solve problems, but with some fundamental differences.
Whichever path you choose, you’ll need to gather relevant, trusted data from many sources quickly, easily, and securely.
We hope you like this easy take on explaining Artificial Intelligence. If you’d love to read more such articles, check out our blog page to find out more!