Top Application Cases for the Data Science Industry

In describing the role of data science, Mike Loukides, VP at O’Reilly Media, said: “Data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.” That, in essence, sums up what the field is about and why it is getting the attention it does.

The new world gets a lot of its direction from data science, which should not be surprising when considering the vast amounts of data that flow into organizations across sectors. From giants such as Amazon, Facebook, and Google, to those much smaller in size, the data science industry has a number of takers. This also explains why the jobs of data science professionals are among the most demanded in the digital era.

But what exactly is data science? It refers to the totality of algorithms, machine learning (ML) principles, and other data science tools that work to uncover patterns hidden inside raw data, in the search for strategic insights. Data must be extracted, maintained, analyzed, and visualized in a scientific manner.

Users of data science vary not just in size but in sectors too. From agriculture to telecom, and from ecommerce to weather forecasting, a massive variety of industries are either looking to incorporate data science into their operations or are already on the way to capitalizing on its benefits. It is no wonder then that the job of a data scientist is highly sought after.

Why is data science really needed?

Essentially because till not so long ago, organizations possessed data that was largely structured and small, and thus easily handled by business intelligence (BI) tools. However, huge volumes of unstructured data in the digital world of today are well beyond the capacity of simple BI tools. The task thus falls to data science tools such as advanced algorithms and complex analyses.

Across sectors and organizations, big data is flowing in, and it must be studied thoroughly to understand how to proceed. Let us look at the usability of the data science industry in different sectors:

👉Banking: This sector works extensively with data science professionals for insights to improve its product and service offerings, as well as their security. The upshot for customers across the globe is a more positive experience, courtesy analyses of the gathered data. Key application areas for data science here include customer segmentation, fraud detection, and recommendation engines, among many others.

👉Finance: Data and finance are seemingly hand in hand, as finance by definition are based on data. In fact, finance has used data science well before the term actually became popular and recognized. Key application areas include algorithmic trading, customer management, fraud detection, and risk analytics, as well as providing personalized services. ML also finds use in automating processes and maintaining security.

👉Digital marketing: Data science tools can enhance the customer experience by revolutionizing the digital marketing strategies of an organization. Specific use cases include:

· Choosing the right marketing channel

· Identifying the suitable target audience

· Real-time interaction marketing

👉E-commerce: The key contribution of the data science industry here is in terms of better customer targeting. Data science has essentially transformed e-commerce through:

· Identifying a potential customer base

· Understanding product styles and foreseeing their trends

· Forecasting types and quantities of goods and services required, through predictive analytics

· Creating optimized pricing structures

👉Education: Data science professionals can help to shape academic as well as non-academic skills (such as emotional and social skills) in a number of diverse ways. Universities also tap it to bring innovations into the curriculum, monitor the performance of its instructors, and track student requirements.

👉Healthcare: This sector has moved to a whole new level with the power of data science, getting a lot of benefits. Top use cases here include the following:

· Virtual assistance for patients

· Analyzing medical images

· Accurate prognosis and diagnosis towards prescribing predictive medicine

· Managing customer data

· Creating new drugs using data science and ML algorithms

· Genetics and genomic research

· Preventing and tackling diseases

👉Movies: The data science industry plays an important role in turning a movie into a blockbuster. Just like any other sector, this industry needs an improved understanding of its audience so that it may generate improved results. Better films can be developed, more revenue can be earned, and exciting content can be streamed in real-time by Netflix and its kind.

👉Retail: This sector has much to thank data science professionals for, given that it has always benefited from their output. Advanced algorithms facilitate a number of aspects of retail operations, with more than 60% of retailers admitting to earning competitive advantage courtesy data science techniques. Specific tasks include:

· Customer sentiment and market basket analysis

· Fraud detection

· Price optimization

· Recommendation engines

Aside from the above industry examples, there is a huge list of current and potential users of data science tools. It is thus no surprise that a ‘data scientist’ role is considered the sexiest one on the planet!