Business analytics is one of the most growing fields in the modern era. Due to the deadly combination of statistics and computer science the scope of business analytics has been growing wider and wider. This evolution of business analytics has resulted in various kinds of career opportunities that’s why it is very important to understand the meaning and the importance of business analytics.
In this blog, we will be covering the following topics:
- Business Analytics Definition
- Types of Analytics
- The Business Analytics Process
- Applications of Business Analytics
- Career Scope in Business Analytics
- Business Analytics Salaries
- Skills Required for Business Analytics
Business Analytics Definition
In this introduction to Business Analytics, we first have to understand the term ‘analytics.’ Now, analytics generally refers to the science of manipulating data by applying different models and statistical formulae on it to find insights. These insights are the key factors that help us solve various problems. These problems may be of many types, and when we work with data to find out insights to solve business-related problems, we are actually doing Business Analytics.
A simple example of Business Analytics would be working with data to find out what would be the optimal price point for a product that a company is about to launch. While doing this research, there are a lot of factors that it would have to take into consideration before arriving at a solution.
Check out this quick guide to a Business Analytics career:
Types of Analytics
There are various types of analytics that are performed on a daily basis across many companies. Let’s understand each of one of them in this section.
Whenever we are trying to answer questions such as ‘what were the sales figures last year’ or ‘what has occurred before,’ we are basically doing descriptive analysis. In descriptive analysis, we describe or summarize the past data and transform it into easily comprehensible forms, such as charts or graphs.
An example would be finding out the percentage of leads that we couldn’t convert and the potential amount of business that we lost due to this.
Predictive analytics is exactly how it sounds like. It is that side of Business Analytics where we make predictions about a future event. An example of predictive analytics would be calculating the expected sales figures for the upcoming fiscal year. This is majorly used to set up expectations and follow proper processes and measures to meet those expectations.
In the case of prescriptive analytics, we make use of simulation, data modeling, and optimization of algorithms to find answers to questions like ‘what needs to be done.’ This is used to provide solutions and identify the potential results of those solutions. This field of Business Analytics has recently surfaced and is on a heavy rise as it gives businesses multiple solutions to their problems with their possible effectiveness. Hence, if let’s say Plan A fails or they don’t have resources to execute it, then they would still have Plan B, Plan C, etc. in hand.
In short, Business Analytics is a combination of all of these types of analytics also known as types of Business Analytics.
The Business Analytics Process
Just like for any action in a business there is a process involved, in Business Analytics also there is a process. The same as other processes, Business Analytics needs to be systematic, organized, and include step-by-step actions so that we have the most optimized result at the end with the least amount of discrepancies.
Now, let’s dive into the steps involved in Business Analytics:
- Business problem framing: In this step, we basically find out what business problem we are trying to solve, e.g., when we are looking to find out why the supply chain isn’t as effective as it should be or why we are losing sales. This discussion generally happens with stakeholders when they realize inefficiency in any part of the business.
- Analytics problem framing: Once we have the problem statement, what we need to think of next is how analytics can be done for this Business Analytics problem. Here, we look for metrics and specific points that we need to analyze.
- Data: The moment we identify the problem in terms of what needs to be analyzed, the next thing that we need is data, which needs to be analyzed. In this step, not only do we obtain data from various data sources but also we will clean the data (as in, if the raw data is corrupted or has false values, we remove those problems and convert the data into usable forms).
- Methodology selection and model building: Once the data gets ready, the tricky part begins. In this stage, we need to determine what methods have to be used and what metrics are the crucial ones. If required, the team has to build custom models to find out specific methods suited to respective operations. Many times, the kind of data we possess also dictates the methodology that can be used to do Business Analytics. Most organizations make multiple models and compare them based on the crucial metrics decided on.
- Deployment: Post the selection of the model and the statistical ways of analyzing the data for the solution, the next thing we need to do is to test the solution in a real-time scenario. For that, we deploy the models on the data and look for different kinds of insights. Based on the metrics and the data highlights, we need to decide the optimum strategy to solve our problem and implement the solution effectively. Even in this phase of Business Analytics, we will compare the expected output with the real-time output. Later, based on this, we will decide if there is a need to reiterate and modify the solution or if we can go on with the implementation of the same.
Applications of Business Analytics
Business Analytics is a very useful process followed and implemented by different kinds of sectors. Whether it be the IT world, the healthcare domain, or any other types of business, it can help improve them immensely. Hence, there are a vast number of applications for Business Analytics. Some of the notable Business Analytics examples are:
- Optimization of supply chains
- Forecasting revenue
- Pinpointing reasons for employee attrition
- Fraud detection
- Recommendation systems
- Finding out the number of cabs required in a region
- Price point comparison and more
Looking to get started with Business Analytics? Read our blog at Learn Business Analytics now.
Career Scope of Business Analytics
As we mentioned above, there are a lot of different sectors recruiting professionals for their Business Analytics team hence the career scope of business analytics is very wide. These professionals are hired for different kinds of job roles. Their responsibilities may differ a little based on their designation and the sector in which their organization operates, but the end goal is the same: Supporting their Business Analytics team to solve business problems.
Roles Within the Analytics Team
|Business Analyst||Developing visualizations, building APIs, and creating and working with dashboards|
|Data Analyst||Analyzing data trends and finding valuable insights and metrics|
|Decision Analytics Professional||Working with data and client requirements to find out the optimum path for a solution and its implementation|
|Business Consultant||Working with partner clients from planning to implementation phases|
Learn more about careers in Business Analytics on our blog at Business Analytics Careers.
Business Analytics Salaries
- The average salary in the Business Analytics field is ₹7.8 LPA. However, it may vary based on the sector and the experience and skills of the candidates.
- As they go higher in their career, these professionals can easily touch a point of ₹20 LPA with 6–7 years of experience.
- Candidates with Python and R skills earn higher average salaries than those who do not have these skills.
- In the United States, the average salary of a Business Analytics professional is around US$80,000 per year.
Skills Required to Enter the Field of Business Analytics
The skillset of a Business Analytics professional include:
- SQL (mandatory)
- MS Excel
- Statistical expertise
- Strong analytical skills
- Business acumen
- Python coding (preferred by a lot of companies)
- Proficiency in R (preferred by a lot of companies)
- Data visualization skills (preferably in Tableau and Power BI)
These skills are very easy to master if you are ready to acquire them. You can further enroll in our Business Analyst Course to become a Business Analyst professional.