Business Analytics and Data Analytics are two specialised disciplines with distinct yet overlapping goals and objectives. Business analytics entails the utilization of statistical analysis and historical data to investigate an organization’s past performance with an aim to extract key insights that can facilitate business planning and decision-making. Opting for business analyst as a career would mean undertaking a deep dive into business-specific domains to identify optimization opportunities & problems that affect an organization’s processes & systems and addressing such problems with the help of technology-based solutions in the form of architectural upgrades, implementation of new tools, deployment of software applications etc.
On the other hand, data analytics concerns the extracting, cleansing, transforming, analysing and modelling of raw data into valuable insights that help businesses make logical conclusions and well-informed decisions. Typically, the job description of a data analyst role involves examination of large sets of structured and unstructured data, usually derived from diverse and fragmented sources, to reveal hidden trends, patterns and meaningful correlations that are embedded in the data sets. By leveraging techniques like text mining and data visualization, information is extracted and classified quickly and presented in a form that is easily accessible, comprehensible and utilizable for the users. The specialised discipline makes extensive use of predictive analytics with its array of statistical techniques like predictive modelling, machine learning (study, creation and use of automated algorithms) and data mining to analyse present and historical data for accurate prediction of future trends and events. It also exploits various other statistical approaches and hypothesis testing like exploratory data analysis (EDA) and confirmatory data analysis (CDA) to enable researchers and scientists to analyse & compare data sets and draw statistical inferences that help them corroborate and/or invalidate existing theories and hypotheses.
As evident from the above, business analytics is more focused on resolving typical business challenges while data analytics encompasses a broader focus. While the two disciplines may vary in scope, they are also similar in many aspects. Both are heavily dependent on the availability of large volumes of high quality data that can be explored and investigated to extract necessary insights and inferences that are required to drive and fulfil business outcomes. Both the disciplines harness business intelligence, OLAP (online analytical processing), predictive modelling, statistical analysis and advanced analytics comprehensively. Likewise, both share a common vision – to help organizations become more efficient, productive & profitable and to provide businesses with a competitive edge by empowering them with cutting-edge insights into evolving and upcoming market trends that allow enterprises to respond to such trends quickly with well-informed decisions.
Considering the similarities that characterize the two fields, certain skills are common to the role of a business analyst and that of a data analyst. If your are planning to choose business analyst as a career path or are aspiring for a career as a data analyst in India, then here are few skills that you must possess or acquire to make it big in any of these two domains.
Strong Communication and Problem-Solving Skills
Data analyst jobs and business analyst jobs require extensive communication, both in person and over calls, emails and web meetings. To see through your job deliverable successfully, you will have to negotiate and collaborate effectively with various stakeholders, including clients, internal management, team members and developers. Facilitating work-related meetings, listening & probing effectively to assimilate information and articulating requests clearly & in the appropriate forum are some of the common expectations from a data analyst or a business analyst. Thus, excellent communication skills are imperative if you aim to flourish in these fields.
Equally important is your ability to examine a problem from different points of view and your aptitude to delve deeper into an issue to review it in its entirety in order to reveal the underlying causes. Critical thinking skills are non-negotiable here because they enable you to explore multiple options and help you make a sound judgement of selecting the most viable solution that is best suited to mitigate the issue at hand.
Willingness to Explore and Creative Bent of Mind
To succeed in your career as a business analyst or a data analyst, you must possess deep-rooted curiosity to unearth new facts and insights. Such a bent of mind will inspire you to question the status-quo. It will stimulate you to think out of the box and come up with novel and creative ways to visualize, analyse and interpret data in order to derive crucial trends and patterns that are otherwise hard to discern with a hackneyed mindset.
Knowledge of Programming Languages
While it’s true that not every data or business analyst role might require one to be an expert in coding or executing database queries, yet it is a fact that the role of a data analyst or a business analyst often demands proficiency in programming languages. It helps if you are well versed with the likes of Python, Scala, R, SQL, Java, C++ etc. in order to be able to work with voluminous data sets in a competent manner.
Quantitative and Qualitative Skills
It goes without saying that strong analytical skills, both quantitative and qualitative, are vital for anyone who decides to venture into data analytics or business analytics. Becoming a data analyst would need you to acclimatise yourself with a variety of data analytics software and methodologies, predictive modelling tools and statistical tools & techniques such as descriptive statistics, EDA and CDA that are required to undertake a detailed inspection of data. Similarly, becoming a business analyst would necessitate a sound grasp of statistical methods and tools like explanatory and predictive modelling as well as robust documentation and specification skills. Both the disciplines mandate you to demonstrate prowess in numerical analysis and interpretive skills so that you are able to comprehend and analyse numerical and non-numerical data swiftly and accurately.
Lastly, enrolling in a professional skill enhancement course like MIT Skills’ Advanced Post Graduate Program in Data Analytics will help you master crucial data science skills like data mining, data modelling, data architecture, data extraction, data transformation, data visualization, data interpretation and business intelligence development within a short time frame of 6 – 8 months. The concise course can be availed by B.Tech./B.E./ M.Sc./MBA students or by any graduate with a minimum of 50% grades. MIT Skills’ comprehensive course curriculum will empower you with essential data science concepts such as Statistics Theory, Hadoop/HDFS/Hive Architecture, SQL Spark , Base SAS, SAS SQL, SAS Macros, R Studio, Data visualization with Tableau Python Scikit LEARN, Machine Learning algorithms : Naïve Bayes Classifier Algorithm, K Means Clustering Algorithm, Support Vector Machine Algorithm, Linear Regression, Logistic Regression, Random Forests, Decision Trees, Advance Excel to make you industry-ready and employable across a range of industries and business sectors