Examine the Applications of Data Science

Almost every industry, from advertising to manufacturing, relies on data to operate. With the number of applications ever-increasing, the ability to extract meaningful data is becoming even more important to improve business decisions and inform strategy in every field.

Watch Etienne Pienaar, Convenor on the Data Science with Python online short course from the University of Cape Town, discuss the application of data science in modern businesses.

Transcript

By now you’re probably aware of the hype around data science, with exciting futuristic-sounding nomenclature, such as machine learning and artificial intelligence. Big data and statistical analysis have become critical components in the functioning of virtually all modern businesses, with applications spanning fields ranging from manufacturing, optimisation, operations research, and retail to insurance and banking.

As a consequence of the dependence of modern business on data, the number of applications of data science in the industry is too large to numerate in a single video. However, some notable fields cover everything from customer segmentation for targeted advertising to fault detection in manufacturing.

Data science is also well-established in the financial services industry. Banks use popular modelling techniques for everything from revenue forecasting and credit card fraud detection to calculating credit risk, both in traditional lending schemes as well as modern financial products, such as micro-loans.

The cutting edge of data science is perhaps most notably in the tech industry, with both the theoretical and the physical data science technologies, i.e. the algorithms and the hardware, directly integrated into the day-to-day running of such companies and the products that they offer. Quite a number of the algorithms in a modern-day data scientist’s toolbox can trace their origin to various tech industry problems.

Some obvious examples are recommendation systems and web search, and more recently automated image\video processing and security. So, data science leverages statistical analysis of large amounts of data in order to either augment, streamline, or even create the value chain in modern industry. This is achieved by making use of algorithms to identify patterns in data that give useful telemetry for the implementation of high-level cognitive functions, such as strategy and decision-making, as well as low-level productive functions, such as physical products or services.

For these purposes, it’s useful to think of businesses as free-market machines, and data science as a key component in the nervous system of such machines. The number of applications of data science is ever increasing, and identifying how data science can be applied in your particular industry is a useful skill itself.

Can you think of any potential applications to your particular domain of expertise? Where could your organisation benefit from data science?