What Is a Business
Analyst?
Business Analytics is one of the most
growing fields in the modern era. The scope of business analysis is getting
wider and wider due to the deadly combination of statistics and computer
science. This development of business analytics has resulted in a wide variety
of career opportunities. Therefore it is very important to understand the
meaning and importance of business analytics.
Before knowing
about Business Analytics First know about analytics
In this introduction to Business
Analytics, we have to first understand the term 'analytics'. Now, analytics
generally refers to the science of manipulating data by applying various models
and statistical formulas to find insights. These insights are the major factors
that help us to solve various problems.
Definition of
Business Analytics:
When we work with data to find
insights and solve business related problems, we are actually doing business
analytics. Tools used for analytics can range from spreadsheets to predictive
analytics for complex business problems. The process involves using these tools
to create patterns and identify relationships.
Tasks and duties
can include:
- A
simple example of business analytics would be to work with data to find
out what would be the optimal price point for a product a company would
launch. When doing this research, several factors need to be taken into
account before arriving at a solution.
- how many and which customers
are likely to unsubscribe
- and working with available
data to detect and evaluateIs doing how and why the tastes and preferences
of customers who regularly visit a particular restaurant change.
Components of
Business Analytics
·
Data Storage- Data is stored by the computer in
such a way that it can be used further in the future. The processing of this
data using storage devices is known as data storage. Object storage, block
storage, etc. are some of the storage products and services.
·
Data Visualization- It is the process
of graphically drawing information or insights drawn through the analysis of
data. Data visualization eases the communication of output to management in
simple words.
·
Insights- Insights are the outputs
and conclusions drawn from the analysis of data by applying business analysis
techniques and tools.
·
Data Security - One of the most important
components of business analytics is data security. This includes monitoring and
identifying malicious activities in the security network. Real-time data and
predictive modeling techniques are used to identify vulnerabilities in systems.
Types of Business
Analytics
There are different types of
analytics that are performed on a daily basis in many companies. Let us
understand each of them in this section.
Descriptive
Analytics
Whenever we're trying to answer
questions like "what were the sales figures last year" or: what's
happened in the past, we're basically doing descriptive analysis. In
descriptive analysis, we describe or summarize past data and transform it into
easily understandable forms, such as charts or graphs.
An example would be finding out what
percentage of leads we could not convert and the potential amount of business
we lost because of it.
Predictive
Analytics
Predictive Analytics is exactly what
it sounds like. This is the side of business analytics where predictions are
made about the future event. An example of predictive analysis is calculating
expected sales figures for the upcoming fiscal year. Predictive analysis is
primarily used to establish expectations and follow appropriate procedures and
measures to meet those expectations.
Prescriptive Analytics
In the case of prescriptive
analytics, we use simulations, data modeling and optimization of algorithms to
find answers to questions such as "what needs to be done". It is used
to provide solutions and to identify the possible consequences of those
solutions. This area of business analysis has come to the fore recently and
is on a huge growth as it gives many solutions to the problems faced by
businesses, along with their potential effectiveness. Suppose plan A fails or
there are not enough resources to execute it, then plan B, plan C, etc. are
still at hand.
The Business
Analytics Process
Like anything else in business, there
is a process involved in business analysis. Business analysis needs to be
systematic, systematic and incorporate step-by-step actions to achieve the most
optimized results in the end with the least discrepancies.
Now, let's dive into the steps
involved in Business Analytics:
- Business Problem Framing: In this step, we basically figure out what business problem we are
trying to solve, for example, when we want to find out why the supply
chain is not as effective as it should be or we Why are you losing sales?
This discussion usually takes place with stakeholders when they realize an
inefficiency in any part of the business.
- Analytics Problem Framing:Once we have the description of
the problem, we need to think ahead about how the analysis can be done for
that 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 the need for analysis, the next thing we need is the data that
needs to be analyzed. In this step, we not only get the data from
different data sources but we also clear the data; If the raw data is
corrupt or has incorrect values, we fix those problems and convert the
data into a usable form.
- Methodology selection and
model building: Once the data is ready, the tricky part begins. At this stage, we
need to determine which methods are to be used and which metrics are
important. If necessary, the team will have to build custom models to
explore specific ways that are suited to the respective tasks. Oftentimes,
the type of data we have also determines the methodology that can be used
to conduct business analysis. Most organizations create multiple models
and compare them based on critically important metrics.
- Deployment: Post the statistical methods of
selecting the model for the solution and analyzing the data, the next
thing we need to do is test the solution in a real-time scenario. For
that, we deploy the model to the data and look for different types of
insights. Based on the metrics and data highlights, we need to decide on
the optimal 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 whether the solution needs to be replicated and modified or we can
proceed with the implementation of the same.
Applications of
Business Analytics
Business analytics is a very useful
process which is used in various fields. Be it the IT sector, the healthcare
sector, or any other type of business, business analysis can help them make a
difference. Therefore, there are a huge number of applications for business
analytics. Some notable examples of business analysis are:
- Optimizing supply chains
- Forecasting Revenue Indicating
- employee reasons for leaving
- Fraud Detection
- Recommendation System
- the number of cabs required in an area
- Price point comparison
Business Analytics
v/s Data Analytics
Business Analytics Means to conduct
data analysis to draw business insights and offer solutions to complex business
problems. This specifically involves dealing with business insights, as opposed
to data analytics.
Data analytics refers to the analysis
of already existing data to draw conclusions about the information contained in
the data. It is a broad concept and also includes business analytics.
Business Analytics
v/s Data Science Data Science
refers to the performance of data
analysis using advanced statistical methods and accessing insights to make
data-driven decisions. This is the advanced stage of business analytics.
However, both the roles differ based on the activities and tasks involved in
making business decisions. Both play a very important role in understanding the
fundamental difference inherent in Business Analytics and Data Science.
Data Science explores potential
solutions and generally aims at long-term problems and business development. In
contrast, business analysis aims at solving short-term and specific business
problems.
Career Scope of
Business Analytics
As we mentioned above, there are many
different areas to recruit business analytics professionals. Hence, the career
scope of business analytics is very broad. Business analytics professionals are
hired for a variety of job roles. Their responsibilities may vary slightly
depending on their designation and the area in which their organization
operates, but the end goal is the same – solving business problems.
Some Important
Roles in Business Analytics
|
Designation |
Description |
|
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 |
Skills Required to
Enter the Field of Business Analytics
- 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)
Business Analytics
Salaries
- The
average salary in the Business Analytics field is ₹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.