Data analytics is a fairly new independent discipline. It allied with computer sciences by a mutually beneficial proposition of progress. Data is everything when it comes to predicting a way through the tough times we are experiencing right now. Data is key to survival for new businesses and commercial organizations due to the precarious state of today’s economy. The need for putting data to good use has given birth to the dedicated data-dependent roles of a business analyst and a data analyst. Right now, all the businesses both old and new who are concerned about growth and survival are leaning towards a more data-driven future. Becoming a data analyst is not an easy venture to undertake. However, data-literate people from any background can become data analysts with the right kind of training. And due to the versatility of a data analyst, the role is becoming more and more popular by the day. This article will discuss the reasons for the same and compare the phenomenon with the established discipline of business analysis.
Why data analytics over business analytics?
A business analyst is expected to be a good manager. A manager with great statistical and data science prowess. But there are severe limitations to the role as business analysts deal with business data primarily. Most of the time ignoring other factors like geographical, cultural and biological pieces of information. This limitation prevents a business analyst from deploying before any business is conducted. Thus a business analyst can suggest changes to a product while upgrading, devise a marketing strategy with the help of data and maybe work for better overall efficiency as well. But for new ventures and startups, there is not much in-house business data available and not much room for a business analyst to excel.
On the other hand, a data analyst can be deployed even before the inception of a business. The regional data containing historical geographical and population data can be put to good use even whole designing a product or pricing the same. In 2022 the prospects of taking chances with money are very poor. And for the startups and new budding ventures, a bad move can end it all. Thus a data analyst is always prefered for their versatility. However, a data analyst is not expected to be a good manager and concentrate only on analysis and representing data.
Is data analyst a good career?
One short answer to this question is yes. A career in data analytics can change one’s life completely and raise the standard of living by a huge margin. Data analytics is a discipline concerned with huge amounts of data. Often the data is impossible to handle with human efforts. Thus machine learning tools and AI entities are being deployed for assistance. Thus training with the same is required for becoming a data analyst. This training determines the scope of diversification career security and work-life balance. The field is driven by skill and dedication thus thrones willing to commit themselves might never be dissatisfied.
Business analytics: still formidable?
Despite all the limitations business analytics is excelling in the field of commerce. Firstly, the managerial skills of a business analyst can prove to be an asset to any venture and definitely worth a high salary. Established businesses learned the lesson of data dependency the hard way after the pandemic. Lack of prediction and little consideration of natural calamity such as COVID19 resulted in a great financial calamity. Thus big businesses are leaning towards data for predictions. A business analyst, due to the managerial promises gained great attention after the pandemic kicked in full swing. But it was solely restricted to big and already established ventures. With hands-on experience and a well developed, tested set of skills it is possible for new business analysts to land jobs with fair CTCs.
Conclusion
Hands-on experience is essential for data analysts as well. The responsibility a data analyst is bestowed upon require perfection and farsighted decision making. Traits can only be achieved by a long time of hard work and training. Data analysts today, are being preferred by startups and new ventures, where mistakes can translate into termination. Thus it is recommended to look for institutes that are willing to provide their students with industrial exposure and maybe an internship at the end of tenure. It is wise to relocate to a place where data education and industry are thriving together, shoulder to shoulder. As the environment matters the most when skill development is concerned.
