Data Science is an interdisciplinary area that uses scientific methods, processes, algorithms, systems, and machine learning principles to discover hidden patterns, trends, and correlations from the extracted raw data.
Data Science emerges to provide a holistic business vision by gathering and filtering valuable/actionable insights that help predict customer behaviour and identify new revenue opportunities. The result? It will ease the decision-making process and enhance innovation and efficiency.
From 1970 to the middle '90s, the existing data was mostly structured and small in size, which could be analysed using simples BI tools. Today we face a completely different reality, where about 80% of data is unstructured or semi-structured. Check the figure below:
Big Data makes it possible to achieve research results that cover a wide range of issues and tell us much about developments in the world in many different areas. This data is generated from different sources (databases, text files, social media, forms, APIs, browser searches, etc.), and simple BI tools cannot process the large volume and variety of data.
The demand for data science skills has grown significantly over the years. Having advanced analytical tools became essential to process and analyze data. These tools help data scientists find meaningful insights and uncover solutions to business challenges.
Data Scientists not only do the exploratory work to discover relevant insights from data. They also use advanced techniques and algorithms to develop hypotheses, make inferences, and identify customer and market trends. More than analyzing what is currently happening, they are responsible for setting best practices regarding data interpretations.
Data Scientists are a new breed of analytical experts who use industry knowledge, contextual understanding, and predictive assumptions to find trends and manage data from many angles, sometimes not even known earlier. This role is an offshoot of many scientific areas such as mathematics, statistics, and computer science, using the latest technologies (like machine learning and artificial intelligence) to find development solutions and growth within organizations.
We have already seen what Data Science is capable of, but how do we make it useful to us? What are its real-world applications?
In fact, Data Science is revolutionising many industries (see picture below), providing valuable business benefits that can be summoned into three major categories: business efficiency, product creation, and customer experience. The ability to increase efficiency is the highest value opportunity that Data Science brings to an existing business model.
The gathering and generation of large volumes of data have long outpaced our ability to process it manually. The automatic processing and analysis of data is a growing industry all on its own. And guess what? The full potential of Big Data technologies is beyond any business’s ability to realize it without Data Science experts to help.
To be ahead of the curve, it's necessary to have a science team focused on creating and analysing predictive constructs to boost your business efficiency. Being a strong competitor requires implementing all these cutting edge data procedures and taking the best advantage.
Digital marketing enthusiast, crazy online shopper, and a mother of a Siamese baby cat. In my spare time, you can find me riding a bike in the countryside.
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