As we stand on the dawn of the new millennium, businesses are looking to optimize the way they work by utilizing data in unprecedented ways. Business Intelligence (BI) and Business Analytics (BA) are two domains that tap into this growing pool of data to boost business growth and revenue. These two skill sets are becoming increasingly critical for companies around the world.
In 2018, Forbes listed Business Intelligence Analyst as one of the top six data science jobs in the world. However, that term might leave you scratching your head for a while. Is Business Intelligence and Analytics one unified subject, or are they two completely different domains?
To those of us who do not work closely with data science, like those on the management side, business intelligence (BI) and business analytics (BA) might not create the image of two distinct domains but perhaps of two overlapping circles. Although in some sense the image of overlapping circles is not entirely wrong, there are many inherent characteristics which differentiate the two. Business owners should be aware of these so that they can employ them in their best capacities.
Once you get down to the nuts and bolts of the matter, you realize that the fundamental differences between the two make them completely separate subjects with vastly different purposes. It’s like peanut butter and jelly. They might be great together sometimes, but most of the time they are spread on different loaves of bread.
Let’s take a look at what both of these domains are all about and how different they are from each other.
The Basic Difference
BA is an umbrella term that comprises skills, applications, technologies, and practices meant to interact with available data, discovers patterns and insights, and follows through with the appropriate action. BI, on the other hand, is an area that comes under analytics and which focuses on measuring past data and gleaning information to enable structured business planning.
You may also like to read: What is Business Analytics? Different components, tools, skills, and careers.
Intelligence can be used to answer questions like “what happened,” “how it happened,” and “how often it happened.” Analytics can tell you “what will happen if this policy is changed,” “what do we need to do next,” and so on. To be very concise, analytics looks at the future and intelligence looks at the past.
For example, a company sells high-end motorbikes in 12 countries around the world. Business Intelligence provides them with data on sales, returns, costs and customer satisfaction for all these dozen countries. Using business analytics, they can reach a decision on which geographic regions it would be profitable to expand into, and in case the numbers are wrong, where they would feel the least impact if they closed up shop.
Difference in Methodology
Advanced analytics includes technology for data, text and multimedia mining; descriptive, predictive, and prescriptive modeling statistical or quantitative analysis; simulation; and optimization. BI makes use of reporting tools (KPIs, metrics), scorecards, dashboards, automated monitoring, OLAP, and ad hoc query. The kind of knowledge generation in analytics is automatic and manual in intelligence. Despite the differences in outputs and methodologies, both are used to work on big data.
The core group of an organization that is responsible for mitigating risks and taking the company forward uses analytics to deal with unanticipated outcomes and optimize possibilities. BI is limited to generating and distributing automated reports on pre-determined metrics and assumptions. BI can use Excel to show answers for a query by fetching appropriate information from the pool of data; however, it cannot help managers and policymakers to come up with responses to new events.
Moreover, the insights that a person can glean from looking at the Excel sheet will remain with them, as it cannot be utilized for organizational learning or improving processes.
Both domains offer different career paths for a student. Courses in analytics will lead them to be analysts (no prizes for guessing!), data scientists and similar professionals while someone trained in BI technologies can bag the roles of administrator, consultant, or manager.
Knowing the differences between both domains enables students and budding professionals to make the right career choices and helps business users to buy the right technologies and skills for their intended results.
What is the relationship between BI and BA?
Interestingly, there seems to be widespread confusion about the differences between BI and BA. Both Gartner and OLAP, define analytics as a subset of BI. However, as we’ve just explained, there is another line of thought altogether that says that BI is a subset of BA, which is the greater purpose that drives the business forward.
The relationship between BI and BA has been made even more confusing by the rapid rise of new technology in both these domains, as well as a rush to make them more marketable. Therefore, the buzzword ‘intelligence’ seems to be more appealing than the more ubiquitous ‘analytics,’ or perhaps it is easier to capture a broader range of purposes by terming it as BI.
Some industry experts have even defined their relationship as a ‘generation gap.’ While earlier the impetus was on gathering Business Intelligence, the current overload of data thanks to digital disruption has shifted the focus more on gathering actionable insights from the data that is available. In other words, companies were more concerned with finding out what’s going on earlier, but now they want to know what they can do in the future.
In this sense, we can say that Business Analytics has taken over from Business Intelligence as the end purpose of data science.
The Rising Tide of Data Science
We’ve delineated the definition of both BI and BA, and now we will have to leave the interpretation to you. Regardless of whichever term you use to describe the work you’re doing, it is essential to learn about the tools and technology that you need to use to do it more efficiently. The parent domain of both still falls within the field of Data Science, which is one of the most lucrative up-and-coming fields for young professionals.
Being a Data Scientist was ranked as the best job in America by Glass Door for three years in a row. It ranked 4.3 out of 5 for job satisfaction and had a very high base median salary. The situation is similar on a global scale, as more and more companies seek the gold of the future within these data mines.
Business Intelligence and Analytics are key subjects in the field and are very much in demand in the higher echelons of business strategy and management. What makes it an even better prospect is the ready availability of academic courses that will equip you for a career in BA. Online certification courses have made it very easy for anyone to dive into the data science mix, regardless of how busy they are or where they’re located.
One of the most comprehensive online courses around comes from Analytix Labs, which offers a 360 degree Business Analytics course which can serve as the perfect introduction to Data Science. Check it out today to dispel any other doubts you may have about BI and BA.