Big data is the talk of the town nowadays. Whether it’s a huge organization or a mere primary school, it’s hard to find a field where it doesn’t have an impact. The enormous amounts of data people are generating every day is giving power to businesses to enhance their services towards their customers.
Data Analytics and Business Analytics are the two most important sub-fields when we talk about Big Data. While they are often used interchangeably, if you look at them from an industry’s perspective, they have quite a lot of differences.
So, how do they differ from one another? And how do you figure what’s better for yourself? This article will answer all your questions!
Data Analytics and Business Analytics Definitions
Before diving in deep, let’s first define both these in simple terms so you can have an insight into what we’re dealing with.
Data Analytics is merely a name given to the process of combining huge sources of data into one and studying them to find effective patterns in them. These patterns not only help you draw conclusions and form hypotheses, but they also assist you in making important decisions using them.
Data Analytics vs. Business Analytics
As we’ve seen, both the field include Data as their major ingredient and require a high understanding of dealing with it to uncover important trends to help make decisions. So, what exactly is the difference? Where do both these terms part ways? Let’s see.
Well, Data Analytics involves dealing with huge datasets and working on their analysis, sorting, and so on, while business Analytics uses real-life tools and applications which are specific to certain businesses. It concentrates on the big-picture and answers the questions on how to make the business more effective and more customer-friendly.
Unlike data analytics, business analytics doesn’t require using complex tools such as Python or Tableau, and it’s limited to the practical side and bridges the gap between the Data Analytics and the Business Operations.
Which is Better for you?
Well, to be honest, both careers have a bright future ahead given the massive amounts of data we are generating every day and how it’s still on the rise. According to a recent study done, it is estimated that we would be generating around 463 exabytes of data per day globally!
So, if we need to answer the questions about which field amongst the two could be better, you need to be more specific. Do you need to choose it as your career? Are you looking at it from a business point of view? Well, then the answers might get a little specific. Let’s see.
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Data Scientist or Business Analyst? Choosing a Career Path
Again, the answer here is quite relative. It would depend upon your personal goals about where you could perform better. Although the stats on indeed.com show us that the average annual salaries for Business Analysts ($79,291) are slightly higher than Data Analysts ($75,434), money isn’t the only variable we use to measure how good a career path is.
Hence, I’ll list down some of the key responsibilities of both the professional and the areas where they need to be good at if they want to excel in their career. You can see where your strengths lie and easily choose that field.
Some Key Roles of Data Analysts & Business Analysts
- For Data Analysis, you have to have a very in-depth knowledge of data and need to know the tools to the very depth. You cannot have a mere understanding of the tools and while you should master how to use them, you should have the ground level basics as well.
In contrast, Business Analysis doesn’t require you such in-depth knowledge, you just need to analyze the data as much as it’s required for your business purposes and the way it interacts with your business. Dealing with this data won’t require the most basic concepts and knowing important tools that can handle data effectively are enough.
- Business analysis includes various business domains and their experience such as e-commerce, manufacturing, etc. To make insightful decisions, a business analyst needs not only to study the data, but he needs significant experience in the specific industry as well to see what social or economic implications of his decisions are.
On the other hand, a data analyst could be completely unaware of any business whatsoever and his only job is to deal with the data, not caring about what affects his decision might make upon the industry.
- Data analysts need to be proficient in cutting edge technologies such as AI or Data Mining, as they sometimes play a huge role in their work. While the business analysts don’t need a high skill level in such things and rather need to be good in areas such as modeling, requirement gathering, and so on.
- Lastly, data analysts need to ace statistical models and complex mathematics to get a strong grasp on the concepts involved in dealing with data while a more business-side background is preferred if you want to be a business analyst.
So, where do you think your strengths lie at? Are you more or a data analytics person or a business analytics person? Remember, the field you can excel in, is always the better career choice for you!
What’s Better for Taking Business Decisions?
Now that we have seen which field could be better for you if you’re looking to pursue career in it, let’s come down to the real talk and see what path could you walk down if you want to make a business decision.
Well, you might already have figured it out, Business Analytics is far better when it comes to making business decisions! As we saw previously, taking effective business decisions is not just about the data and how you use it, but you need to engage with all levels of the organization as well as the stakeholders. Taking a holistic view of the challenge is necessary to take specific decisions and business analytics is great when it comes to understanding business plans, their goals, the market segment they are targeting, etc.
Data analytics doesn’t include such insight of businesses as to let them make the most effective decision, and it’s more focused on the core principles of data and applying various mathematical operations on them.
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Top 5 Differences Between Data Analytics and Business Analytics
Now that we’ve gone through everything, let’s summarize the main differences so you can have a quick glance and see where the differences actually exist.
|DATA ANALYTICS||BUSINESS ANALYTICS|
|Studying data in-depth using complex statistical methods||Studying data using complex tools on a conceptual level.|
|Identifying and understanding trends in huge datasets.||Evaluating emerging trends from huge datasets|
|Working with technical teams only such as IT and Data Science||Working with Data Science teams and business management teams|
|Suggest process improvements related to specific datasets||Suggesting solutions with regards to specific businesses|
|Have a good experience in IT related fields.||Have experience working business administrations and industry’s domain.|
So, that’s it. We have seen some of the core differences in what are the two most emerging sub-careers of Data Science. We have seen how they differ in application and while seemingly they are not anything more than being able to deal with data, there are actually a handful of things separating them.
Make sure you go through the article thoroughly to know what could be the better pick for you, keeping in view your skills and where you want to see yourself in the future.