Guide to Business Analytics Job Roles 2020

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Guide to business analytics job roles

Business Analytics is often misunderstood with Data Analytics and the sole reason for this article is to bust this myth and educate our avid readers about the exact role of an individual pursuing a career in business analytics.

Definition: What is Business Analytics?

Business Analytics is a process that is carried out to understand business performance, gain insights from it, and then implement it in driving business ahead. The vital thing here is that business analytics focuses on a data-driven approach instead of just making decisions based on experience. Experts have valued business analytics because it determines those datasets which are useful and how they can be used to solve business problems.

A person who is well versed with the knowledge of business analytics is someone capable to understand the reason for the business scenario in the past, can apply statistical expertise to draw actionable insights that can help provide concrete business solutions that would help in increasing the efficiency and revenue of the business. Usually, business analytics refers to the combined usage of management, business, and computer science. Management helps in getting information about the business, whereas computer science helps to provide an analytical approach to it which usually is concerned with data.

Components of Business Analytics :

While there is nothing specific about the components that form the overall idea of business analytics, however, there are some general topics that collectively define business analytics. Using business analytics, we can know the following :

  • Finding out the outliers and patterns in the data using data visualization.
  • Identify correlations between the data for prediction.
  • Provide insights for the next course of action or the next impact.

Here are some of the major components that deal with business analytics :

  • Data Mining: Data mining is a process in which raw data is converted into useful information. This is done by looking into the patterns possessed by the data and using machine learning models and statistics.
    • Classification: This is done when the classifier variables are known and it becomes easier to segregate data on that basis.
    • Regression: It is the process of estimating the relationship between a dependent variable and one or more independent variables.
    • Clustering: This is a type of classification however, in this case, the factors based on which the data should be classified are unknown.
  • Forecasting: In simple terms, it means predicting the future based on the past or present data along with statistical analysis done on the data trends.
  • Predictive Analytics: Predictive Analytics deals with the creation of a predictive model and using it to analyze the data. The models are created and managed in such a way that the result is about the outcome of data based on the learning from the past data and applying statistical calculations to it.
  • Visualization: Data Visualization is one of the key important components of business analytics. It involves looking at the data and finding patterns to draw actionable insights from it. Data Visualization provides a clear picture of the trend being followed by the data and provides an idea about the nature of the data.

business analytics components

Types of Business Analytics :

There are various types of Business Analytics, however, all of them are categorized under three major components namely, descriptive, predictive, prescriptive analytics.

  • Descriptive Analytics is the most basic form of analytics that 90% of the companies have been practicing to understand their business problem. Quite literally, descriptive analysis portrays “what has happened” that has resulted in the position of the business that it is in the current situation. It deals with understanding the past and then learning how it would impact future outcomes. Many companies move to descriptive analysis when they want to see an overall situation of their company by finding out the metrics involved in it and the factors leading to it.
  • However, predictive analytics, much like the name suggests is no less than finding the fate of the business by looking into a crystal ball, however, it involves a subsequent reduction of data and statistical analysis to do so. The accuracy is not supposed to be 100%, however, the analysis that is provided is based on the learnings from the behavior of data in the past. Predictive Analytics is further categorized into Sentiment Analysis, Root cause Analysis, Predictive Modelling, Monte-Carlo Simulation, Forecasting, Data Mining, etc.
  • When it comes to a huge amount of data (what we refer to as Big Data), it could not be feasible to perform the analysis and find out the nearest accurate results. However, big data can help in highlighting the issues and knowing the core reasons for the occurrence of business problems in the first place. Businesses usually use Prescriptive Analysis as a successor to the Predictive Analysis, which helps in getting desirable outcomes and optimizes the process to understand the data limitations and uncertainties. There are various business rules associated with prescriptive analysis and thus, is quite complex in nature as well.

Business Analytics Examples :

There are various industries where a business analyst can express his/her expertise towards this domain and contribute to the betterment of the industry. Here are some of the core industries where business analytics has imprinted its wide range of usage:

  • Sales: Whether someone is a salesperson or a manager in sales, they understand it very well that sales without analyzing the facts are not going to yield better results. A business analyst comes to help in this case as the person looks after the sales figures in the past and analyzes the current scenario to run a model and predict the future outcome if the current trend continued. They also provide a workaround on which areas to target and what could be minimized in order to get more sales and run an effective business.
  • Marketing Strategies: Engaging with the customers makes way for better growth of the business and this happens with the involvement of a business analyst at work. Business Analytics can be applied in order to devise various marketing strategies and knowing what wrong has been undergoing which has slowed down the business or what is the right thing which has been minimal throughout and needs a boost for now.
  • Banking Institutions: Banking institutions require business analysts to perform analysis and understand how to improve their reach and keep their customers engaged to them. Usually, business analysts devise a strategy to find out the credit card users and based on the usage, a statistical calculation is done upon which customers are provided with attractive offers, limit increase options, etc.
  • Supply Chain Management: Whether it is about forecasting the future demand, or about tracking logistics, business analytics has played a vital role in the field of supply chain management. Procuring and shipping of inventory can be well managed using business analytics in a much simpler way by reducing costs, reducing defects, etc.

Challenges faced by Business Analysts in the field of Business Analytics :

With great powers come great responsibilities. These responsibilities often turn to be quite challenging when it comes to doing justice to one’s role as a business analyst. Here are some of the major challenges faced by a person in the domain of business analytics :

  • Data Maintenance: Maintaining data has become the most challenging part of the business. As we are moving further, a huge amount of data is being generated and it has become a cumbersome process to keep the data maintained across all platforms. A single gap in the data structure will create a lot of problems as the whole data becomes meaningless.
  • Education: It is very important to educate people about the severity and requirement of a professional in the field of business analytics. When people will become aware of this, naturally the void for the requirement of business analysts will be filled, thus creating more people to manage a greater amount of data.
  • Access of Information: Usually the analysis related to Big Data is only accessible by the relevant department of an organization which makes it difficult for others to understand the procedure upon which the business is being operated. Business Analytics thus creates a big difference among individuals in the same organization and it possesses a big challenge.
  • Quality of storing data: Storing the data requires an elite quality of maintenance as well. If the data is not well secured or not well maintained, it could lead to missing data, duplication of data, etc.
    Time-consuming: It is very time-consuming to extract data, clean it, and then put it to analyze. While this process was not enough, nowadays, creating graphs have been treated as the final outcome of data presentation which has just added to the time-consuming factor.

Business Analytics Tools :

There are many tools that are used for the purpose of business analytics. These tools are based on their industry usage and ease of analysis.

  • R: R is one of the most popular tools in the analytics industry. The most versatile among its competitors, R is known to be the most efficient tool when it comes to managing huge datasets. There are about 8000 packages available for R now. The credibility of the R language has improved during mid-2015.

R logo

  • Python: Python is termed to be the easiest programming language by industry experts. It is quite fast and it developed its base into an analytics tool with libraries like NumPy, SciPy, etc. In today’s date, we can perform a lot more statistical and mathematical functions. Python has been the most favorite choice among the industry experts because most of the people who are migrating to the data science field from the programming background have already got their expertise in Python.

python logo

  • Apache Spark: Spark is an open-source processing engine that has its own machine learning library and it makes way for analytics. It deals with unstructured data or a large number of data. The biggest advantage of Spark has been its easy integration with the Hadoop ecosystem.

apache spark

  • Apache Storm: Storm is the tool of choice when the data is dynamic. It is ideal when real-time analytics or stream processing is concerned.

apache storm logo

  • PIG and HIVE: The advantage of using PIG/HIVE is that it helps in the reduction of the complexity of writing MapReduce queries. Both these languages are similar to SQL. Most companies that work with Big Data use Pig or Hive.

apache hive logo

Careers in Business Analytics :

There is a huge demand for the work of business analytics followed by huge growth. Here are some of the careers in the field of business analytics.

  • Big Data Engineer: As the name suggests, a person employed as a Big Data Engineer is supposed to manage the framework and data within the organization.
  • Financial Analyst: A financial analyst is supposed to look after the financial data of the company and then use statistical models to understand the nature of the business and its financial strength and capacity.
  • Marketing Analytics Manager: This job role makes the person responsible for creating and managing data related to marketing campaigns and then analyze them in order to understand the growth of the business.
  • Business Intelligence and Analytics Consultant: It involves creating models and implementing technical solutions.
  • Fraud Analyst: Usually employed by banking institutions, fraud analysts are the type of business analysts who try to find out the fraud happening in credit cards, bank accounts and develop models on how to minimize them.
  • Retail Sales Analyst
  • Statistician
  • Data Scientist: A person is termed as a Data Scientist who moves into the research analysis of data and focuses on deep learning. A data scientist is expected to study more on the existing practices and devise newer methods, calculations, models, that would serve useful to the business analytics community.
  • Data Visualization Analyst: A data visualization analyst as the name suggests, is concerned with viewing the trends of data and understanding the nature of it. They find out the outliers associated with the data and also check for the correlation between two variables. This helps in understanding the business in a better way and helps business analysts to devise new steps in order to ensure better business reach.

business analytics job roles

While the role more or less differs as per the designation, however, the one thing that remains common across all of them is business analytics.

If you are looking to get certified in a business analytics course and get recognized with your skills, we recommend you to go for a Business Analytics certification course from Ivy Professional School. You can also get in touch with us at +91-7676882222.

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