Business analytics simply refers to the use of tools and techniques to turn data into meaningful business insights.
Earlier it involved the collection and exploration of organizational and transactional data with the help of statistical models; presently it also takes into account the unstructured data sources like social media and different social forums.
With advent of machine learning and deep learning, businesses also deploy advanced analytics or data science methods to analyse and make of use text, voice and image data from unconventional data sources.
Business analytics is kind of a hybrid term which derives from both business intelligence and data analytics -BA retains certain features of both these fields while being distinctly recognizable discipline itself.
There is a severe lack of clarity when it comes to business analytics; a number of questions tax the enthusiasts. We will address some such questions and try to find adequate answers to them.
Why is Business Analytics Necessary?
Every business has some goals and some hindrances which stop it from reaching those goals.
The job of a business analyst is to find those problems with the help of data and to recommend probable solutions.
And, the speciality of business analytics lies in its ability to make recommendations based on factual data analysis.
It is one thing to sift through a large amount of data and find some patterns and a totally different thing to relate those patterns with a certain business related problem and then offer a solution.
Not only does it take command of statistical tools but also a keen, business oriented vision. A business analytics professional builds a bridge between analytics skills and business acumen which is necessary for data driven companies to attain success.
How does Business Analytics Work?
A business analyst has to go through certain loosely structured steps in order to make most of his or her post.
The first step is of course locating the problems. These problems can be related to the supply chain, sales, product optimization or customer engagement.
Once a problem is pointed out the business analyst has to set out to find a plan of action.
This usually includes getting access to data, analyzing it and finding actionable insights.
It basically works on three levels:
This means finding the answer to ‘what has happened?’ by collecting and sorting historical data. This may include data regarding sales, profit and loss, the allotment of funds for different needs, the changes in product design and the results.
Descriptive analysis is absolutely necessary to find out where a business organization stands at a certain point of time.
It also draws correlations between certain decisions and their outcomes thus creating a detailed review of the business processes.
It tries to answer two important questions. ‘What if we let things run as they were?’ and ‘what happens if we change X?’
After describing the current situation, the business analyst finds patterns in the data which help him correlate one metric with another.
Thus it is possible to predict, to a certain measure of accuracy, what will happen if things continue as they were. There can however be new suggestions regarding business processes.
Predictive analysis also finds out the probable results of a certain change. This typically leverages analytics techniques based on statistical models.
It is primarily the forte of a data scientist or an advanced data analytics professional.
But as we move toward a time where the boundary of a certain job profile is becoming increasingly obscure, we cannot really keep a business analyst completely detached from prescriptive analysis.
Similar to predictive analytics, this involves in depth use of statistical and machine learning models to come up with probable suggestions which can drive the company towards its goal.
A simple case study can shed some more light on these aspects
Let us say a company has access to the demographic of consumers which shows their location, jobs, salaries and credit history.
The business analyst comes up with a statistical model that segregates people with different income and different credit scores and goes through their purchase history.
This model then helps correlate a consumer’s income and credit score with the product he or she purchases.
Thus it predicts what a customer falling into a certain income belt may buy and an offer is tailor made for that belt of customers.
This can help the company device better targeted marketing strategy and more effective ad campaigns.
This is a classic example of the predictive quality of a business analytics.
Things will spice up further if we bring some unstructured visual and textual data into play. Suppose there is a series of comments on a number of forums regarding a topic which is closely related to what an organization offers.
These textual messages actually speak volumes about your consumer base, their choices, their orientation and the market trends.
A business analyst can find insights from this sort of information and suggest changes in the business processes and product management. This would be an example of prescriptive analysis.
Are Business Analytics and Business Intelligence the Same?
The answer is a plain and simple ‘no’. We have already stated that business analytics retains certain qualities of business intelligence albeit it is a different discipline.
The key purpose of business intelligence is maintaining the current operations, streamlining the business processes to save time and resources and optimizing business processes to suit the requirements of the present market.
In fact business analytics also deals with the current situation of the market and steps taken to keep things running smoothly.
But it goes a step further and uses big data analytics tools to solve business oriented problems. We can roughly say that business analytics is BI and more. Business analytics training prepares specifically for the job.
How to Distinguish Between Big Data Analyst (BDA) and Business Analyst (BA)?
Like we have already mentioned business analytics involves certain tools and techniques of big data analytics. The job roles of a BA and a BDA can be significantly different.
A data analyst is an umbrella term which takes a wide array of different tasks under its shadow.
The fundamentals of the jobs of BA and a BDA are not mutually exclusive. Both have to explore structured and unstructured data, both are looking to find actionable insights from the data at hand.
The difference is that data analytics can move beyond the idea of a business – it can be related with healthcare, cyber security, defence, traffic control, education etc.
The scope of business analytics is kind of limited by the term business in it. However it does not lose any significance because of this fact.
While Big Data Analysts need a strong command over the analytics tools like Hadoop, Spark, NoSQL, R, Python etc. business analysts depend more on their command of the business processes.
Of course, they need to know the analytical tools at least up to an intermediate level if not advanced level but the key emphasis is on the business acumen.
What are the Key Skills Required to Become a Business Analyst?
We can divide the skills required to become a business analyst roughly into three segments.
- Business Domain Knowledge and Communication Skills
You need an understanding of the niche or domain you are working in. As a business analyst you will be required to understand the inner workings of the market.
You are expected to find the problems in business processes and you cannot achieve that without a holistic idea of the organization, the market and the consumer bases.
Candidates from finance, marketing, or business administration background have a natural upper hand when it comes to business analytics.
Remember you are a bridge between various segments of the organizations therefore it is necessary for you to communicate very well.
- Analytical Tools
A business analyst is required to work with several analytics tools. You can use advanced features of MS Excel, SQL or run your data through Python for real time data processing.
Your business analytics course is responsible to give you a solid foundation with a couple of prominent analytics and data science tools, like MS Excel, SQL, SAS and Python/ R.
- Visualization Skills
Data presentation or visualization is among the most crucial aspects that determine the fate of a business analyst.
With tools like Tableau, data visualization is full of possibilities. Your job does not end at finding data driven insights.
You have to compel your organization to listen to you through your visualization skills. Every use of charts, tables, graphs make a huge impact on the stakeholder’s mind.
What are the Major Challenges Faced by Business Analysts?
Once the business analyst has crossed the first hurdle and located certain problems in the business the obvious next step is to find data that may answer the query.
- Unavailability of Good Data
It often occurs that the data required to solve a problem is not accessible by the business analyst.
It often occurs that the available data is not granular enough which means that you do not get the specific dataset that you required.
The want of good data understandably results into the abundance of messy and garbage data which leads to the next challenge.
- Cleaning Messy Data
Messy data leads to faulty insights. Therefore it is necessary to clean the data.
This usually takes a fair bit of time. But since the data you feed to your system determines the business process, it is worth it.
Whatever may the challenges be, they can be overcome with practice and perseverance.
Business analytics is an expanding discipline with new challenges and possibilities.
The global revenue in business analytics is predicted to reach $ 260 billion by 2022. Keep the confusions at bay and go for it.