Data is changing the world around us. This past year the total volume of data reached 45,000 exabytes – 1 exabyte is 1018 bytes – and this number is only expected to rise. Experts predict this number will double within the next two years as advanced technology is allowing for increased data-storage capacity at reduced costs. With this abundance of data, enterprises can better understand their customers, enabling them to more accurately meet their demands. It is expected that 52% of companies are leveraging predictive analytics in some form and 59% of companies are using Big-Data analytics. The demand for data is only growing, and many companies are using this growing resource to get a leg up on their competitors.

The obvious examples of companies utilizing Big-Data are retailers – Amazon, Target, Walmart – but many other companies have taken advantage of Big-Data to grow their business. Starbucks has a mobile application that gives users the option to order online. Starbucks stores information on the user’s order which is used to make recommendations, as well as speed up service times. When a customer visits a Starbucks, that store’s point-of-sale system is able to identify the customer through their phone and update the barista on that user’s preferred order, leading to reduced wait times and happier customers. Another example is Spotify which uses data on a user’s listening trends to create personalized playlists. Spotify uses a variety of song attributes –energy, liveness, loudness, and even danceability – to find similar songs, leading to more personalized user experiences.

Outside of business, many scientific discoveries have come from Big-Data analytics. Just recently Google DeepMind’s program, called AlphaFold, solved a fifty-year-old problem in biology. For years scientists were trying to predict the shapes of proteins based on their amino-acid sequences. AlphaFold used deep-learning techniques on structural and genetic data to solve the ongoing problem and make predictions that saw an accuracy score of 90 on a 100-point scale (most other teams were seeing 75 points). Solving this problem will accelerate the understanding of cells and allow for faster drug discovery. It will be interesting to see how Big-Data and predictive analytics will benefit companies in an increasingly data-dependent world.

Author: Nick Perinovic