Difference Between Data Analyst and Business AnalystJuly 18, 2019
Data Science is crucial in today’s modern world where AI, ML, VR, AR and CS rule. These sectors are where most career aspirants are seeking to make their careers because of the ever-increasing demand for professionals and the fact that with an increase in data and development of these core sectors, there are plentiful opportunities to land the well-paid jobs.
In the earlier days, data scientists were obscure and restricted in the IT server rooms and department. Today they are the blue-eyed boys in the business world. According to Indeed.com analysis reports, a 4,000 % was reported in this profession. This then justifies why the demand for a trained Data Analyst with domain expertise, mathematical and data engineering skills (who are considered invaluable organizational assets), has been inordinately high. Supply positions are never catching up and their pay packages have seen many a career aspirant’s dreams fulfilled.
An analyst is a specialist in data analysis processing both facts and figures to gauge trends, get gainful insights and make forecasts using predictive analysis. Most people tend to use the two terms business analyst and data analyst interchangeably. Though this can be applied in terms of smaller businesses the “business analyst” in larger enterprises actually covers both systems and data analysis. The scope of the BA is not limited to being only a data analyst but appropriates roles of a data scientist too. What both the analyst and BA do with the data is entirely different and their job skills, the environment of operation and technical skills will definitely differ.
The Role Differences:
The two roles are at NEVER interchangeable in job-roles, and they definitely aren’t the same in terms of career progression, job-scope, payouts, and skills required for the job among other differentiators. The business analyst is definitely better paid since his role demands more and his skills are relatively wider than that of a Data Analyst. To get a better understanding of the job differentiators one needs to look at the job roles of the scientist, analyst and BA.
Data Analyst Role
To manage such large volumes of data and extract information from such data sourced from multiple origins the data analyst is a necessity and a good analyst is a prized corporate asset. Their role in the enterprise is to sift through the data and provide the information, forecasts, predictions and such to the decision makers. The evolution of business strategy and informed decisions is thus dependent on data and the data analyst.
Business Analyst Role
The BA and data analyst roles focus on the use of data in focused roles. The BA assesses data and system infrastructure requirements from a business-perspective. The data analyst, on the other hand, takes interest in the databases and is more focused on placing his insights in the hands of decision makers.
Data analysts are generalists who score over the BA and can tackle more data analysis problems since they have the multi-disciplinary technical skills that include engineering skills of a database engineer, deal with algorithms using the skills of a statistician and have expertise in the data domain/subject matter proficiencies of the data analyst. They focus on insights for business decision making. The BA in addition to being a data analyst also includes focused analysis related decision making on data, systems and infrastructure in decision making.
It is true that a Data Analyst collects databases, manipulates them for foresight and analyzes data for predictions. His presentations, reports, and insights often comprise the latest trends, visualization of the data, and foresight in the form of charts, tables, graphs, histograms and more.
All data jobs need strong business acumen and domain expertise. The technical skills and the level of influence on the organization’s performance mean a good analyst/BA will find the right solution with the most value to the business problems presented.
Mere technical skills and degrees are not enough. Both streams aspirants need to be excellent communicators with the data scientist and analyst who have a problem-solving attitude and can lead from the front. Soft-skills are very important in all teams.
Both data, as well as BAs roles, calls for problem-solving attitude and technical expertise in SAP, PeopleSoft applications and Microsoft Excel suite. The formal educational credential is a graduation or business related degree. An MBA is a plus point.
Becoming a specialized Data Analyst at the reputed Imarticus Learning helps start careers such as business analyst, data scientists, and data analysts. The certification issued at Imarticus is globally accepted as an index of your knowledge and practical skills. So, don’t toss a coin to decide. Explore your career with an Imarticus course. All the best!