In the past few years, big data has changed the landscape of how businesses generally operate – be it in terms of decision making or product development. It’s all because of the unfounded potential of data-backed insights and previously unexplored and neglected findings. This is when both data analysts and business analysts come into play within an enterprise causing freshers to seek data analyst courses online to skyrocket their career in the times of popular demand. But, there’s more to it than that appears on the surface. To understand their distinct roles and the scope of work, it is essential that each facet is looked at in-depth, one at a time. 

It’s a no-brainer that companies churn humongous data sets, irrespective of its industry and home base since they exist. While humans may not have had the right tool or technique to make heads or tails of these never-ending volumes of data, they surely realized the need to store them safely until they evolve the right technology. Rightly heard, necessity indeed is the mother of all inventions. It wasn’t long before that data scientists designed innovative methods that helped them make the most of these wholesome data. 

People may often interchangeably use the terms data analyst and business analyst; both are responsible and industry specialists in two different verticals with a common data link. It’s easier when we learn about them piece by piece.

Who is a Data Analyst?

Data analysts are the mind behind the data derivation and storage. These professionals are deeper into data to draw helpful insights from the otherwise meaningless sets. Every organization has its means of safe-keeping and collecting data from conversions, market research, logistics, and even transactions. And, data analysts are known for their ability to identify hidden patterns, risks or chances from such vast data sets, and then optimize the product/service accordingly for more profits and value. They’re also accountable for understanding people’s demands from the given figures to make the enterprise relevant to the dynamic market. 

Previously, data analysts used to take quite some time to extract a handful of insights from a data set. Thanks to the rapidly growing, high-end technology available in analytics! Now, the same can be done in a matter of minutes. The role of a data analyst includes: 

• Data mining: It is the step when the data needs to be sorted according to their volumes and thus, may help in understanding its relevance, relationship, patterns, etc.
• Predictive analysis: Here, the analyst is known to get into the bottom of past data records to get equipped with the historical actions taken and draw parallels that can bring more outcomes in the future like customer behavior patterns.
  
• Machine learning: A statistical approach to help computers learn the process of data analysis quicker and effectively. 
• Big data analytics: Also termed as the step where the magic happens as data gets transformed into business intelligence. This step involves a series of intermediate events like data mining and machine learning, come together. 
• Text mining: Identify patterns, hidden signs/patterns of events in text-based content like documents and e-mail.

Many other related domains help data analysts immensely create their fast-paced, innovative environment to store, access, and process data. For example – the rapid development of cloud technologies. 

Who is a Business Analyst? 

Like it sounds, business analysis is everything that a company needs to complete its financial goals and drive innovation, with the help of continuous study of enterprises’ data. In this way, a business analyst is responsible for finding loopholes in the existing strategy and continue working together to make the system stable. Since the entire crux of business analysis or the help of business analysis consulting services runs on the big data’s accuracy, it can help you project deeper into your company’s past, present, and future, and make adequate plans.

The main role of a business analyst includes analyzing ‘whats and whys’. In general, business analytics can have three forms – descriptive, predictive, and prescriptive. For every technical or non-technical upgrade, it needs to come approved through several systems for guaranteed results. With the help of machine learning (ML) and other frameworks, a business analyst’s role starts and ends with anticipating future trends and events; to play it out accordingly. On the other hand, the prescriptive analysis is a method to combine the other two – predictive and descriptive analysis as and when required. In general, it may contain mathematical projections, models, and even tradeoffs. 

For a business, all of the above is crucial for its complete development and acquiring higher ROIs. There’s no predefined order or roadmap to which enterprises must adhere to and instead, go equipped and trained as and when required. Currently, several tools and interfaces help you to get deep integration with data sources and make more sense of it. 

Data Analyst vs Business Analyst

With the growing demand for data science in the market and increasing numbers of enterprises realizing the potential of data analysis and tools, both the career options have promising frontier ahead of them.  All you need is the understanding where your interests and strengths lie to pursue it with thorough training.