Role of Data Science in the Business World

How does Data Science power Businesses?

About a few hundred years ago many businesses ran their numbers by simple hand counting. About a hundred years ago businessmen started recording their sales, indexes, and gains in a notebook. Today we use Data Science.

Businesses of the past had restricted domains with their customers being their own townspeople. Now, we have companies operating businesses all around the world. The clients today are customers from every corner of the world. Such a huge influx creates unending information, many of which might not be very useful to the company. As such, there arises a need to sort out the required data to use it in a meaningful manner, and this is where data science steps in.

Data science is categorized as “an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains”. To explain, it is a method of extracting useful information from a stream of fast pacing data and is then applied to multiple applications that are helpful to the company.

However, it is not just the usage of data in a useful way. Data science is a combination of multiple fields such as mathematics, statistics, computer science, programming, and more. It takes elements from all these fields and then combines them together in a manner much more usable and readable to organizations looking to have some structure to their widespread data.

There are multiple factors to Data science and the person performing all these decisions is called a Data scientist. A data scientist is someone who “cracks complex data problems with their strong expertise in certain scientific disciplines (Johari, 2021)”. This suggests that a data scientist is someone who uses expertise in the fields of mathematics and programming to make Data-Driven Decisions.

However, this leads us to the question, what are Data-Driven Decisions? To explain, there is data all around us. From our thoughts to our actions, we all make many small decisions. Have we ever wondered what leads us to those decisions? Surely, it would be through all the choices that were present in front of us, from we chose the one that suited us the best. But how did we determine what suited us the best? We did that via the data that we had collected in our heads. That is what it means to make data-driven decisions.

Similarly, when an organization decides after carefully examining the collected data, the organization is termed to have made a data-driven decision. A data-driven decision, hence, is “defined as using facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives”. It is important for an organization to make real-time decisions from the feedback they receive in data form. It can help them with enhanced communications, unrivaled adaptability as well as new business opportunities.

However, one must not make data-driven decisions the only usage of data science. Though still in its infancy, the applications of data science are far more than what we previously imagined them to be. It does not only provide structured data to an organization but rather a wide range of applications. In fact, Data science is embedded deep in our world, from the management department of an organization to its accounts department. Even health care uses Data science to its core.

We talked about data science making the unstructured data readable for a company, however, it also makes for smarter decisions. One thing that needs to be understood is that data-driven decisions are different from smarter decisions. When the data is structured in a useable format, data science allows for organizations to analyze the information on a large scale which leads to making strategic policies and smart decisions targeting the interests of their clients.

Moreover, with companies making smarter decisions, their products gain better qualities. This is done via analysis of customer reviews through the analytical tools of Data Science. This makes the strenuous process of feedback a lot faster and easier.

Not only this but the plethora of information that companies have today makes them burdened. Too much data buries the much-needed information however data science allows for hidden patterns in the collected data to be unearthed that can predict the success rate of their strategies.

The businesses of today are making quick use of the huge influx of data streaming every second and using it to their advantage. Much like many other technologies in their beginnings, Data science promises a bright future.

Blog credit goes to Aiman Karim, PR Specialist at Ai DataYard