Data is synonymous with power in our times. More data put to good use means more efficiency and more power to predict the future path correctly. Especially during these horrific lockdowns, the locked-down populations started craving for the products and services they need at their doorstep. The existing businesses and commercial organizations thus started racing to become more efficient and reach more relevant people in minimum time and effort. What we are discussing is not just business data. All kinds of data can be utilized in order to bring in the promise of efficiency in day to day tasks. The handling of this huge amount of data required specialized attention and due to these needs business analytics and data analytics rose up as independent disciplines. Gradually business analysts and data analysts became the backbone of most new ventures. And today these roles are essential for running a business with optimum safety in mind. This article will discuss the differences between these two roles and shed light upon the data analysis process as a whole. Asn elaborate, why are data analysts getting more attention than business analysts during these tumultuous times?
Major differences between the roles
A business analyst is expected to be a good manager with commendable analytical and statistical skills. What differentiates a business analyst is the skill of data analysis and making decisions based upon that. A business analyst deals with past business data and decides upon the future way of conducting commerce. The past business data might include sales and marketing data as well as user feedback data. A business analyst makes sense of this data and tries to figure out the ideal package able to satisfy both the customer and the commercial entity.
In addition to that, the flow of data translated in a comprehensive manner falls under the responsibilities of a business analyst. A business analyst can decide what changes can be and should be made to a particular product or service and may be the pricing of a particular product keeping multiple interests in mind.
On the other hand, a data analyst deals with all kinds of data. Data is available even before any commerce is conducted. These massive sets of data can include geographical data, climate and weather data and even data related to health and the economy. By analysis of this huge amount of data, a data analyst can understand the purchasing habits and powers of an entire population. Based on this analysis a new business can design its products and deliver just what a consumer would like to have. The preexisting knowledge regarding the needs of an entire population can lead to the inception of a perfect business model and just periodic up-gradation can sustain these models for a fairly long time. Fortunately, people strong in statistics from any background can become data analysts with experience and a data analytics certification.
How is the analytics performed?
There are three major steps in any data analytics paradigm. The first step is descriptive analytics. In this stage, the unstructured raw data is transformed into structured data sets able to handle the deployment of machine learning tools. And after the data set is arranged, machine learning tools can be deployed for extracting information. Which is followed by the next step in data analytics. Predictive analytics is the stage where predictions are made based on the data analysis done in the previous stage. During this stage, the analyzed data is looked upon and the meaning is deciphered. And after completion of this process prescriptions are made in the next stage known as prescriptive analytics. During this stage, the analyzed data is looked upon with care and conclusions are made on how to proceed and approach the upcoming time.
Why is data analytics gaining more popularity?
The answer is versatility. A data analyst can work with any kind of data and make predictions for multiple scenarios. With or without the presence of business data, a data analyst can help in the inception of the perfect products with the help of population-related data. New ventures too afraid to lose the ground they have occupied are seen to seek help from data analytics and make things more secure for them. As a result, the popularity and demand for data analytics certification are seen to be increasing by the day. A new venture with limited funds will most likely try to hire a data analyst as they can become managers with experience and can be deployed under any circumstances without a second thought.