The global big data service market will grow by 15 % in the next five years, says Bloomberg. In the same report, it predicts a 7,6 % compound annual growth rate (CAGR) for the big data software market and a 9,6 % CAGR for the big data security market. 

Data-driven companies generate tonnes of new data every single day. Some accumulate data about their customers. Some generate data to develop their products. They all find themselves in an urgent need to scale their storages and migrate their data. Which industries are particularly affected?

Internet of Things (IoT)

Each IoT device sends thousands of background messages per day. IoT startups struggle to find a data solution that will satisfy their needs for a real-time database without cost explosion. 

Aerospace

Turbine failure simulations involve huge data volumes and require edge computing abilities. Funny enough, the biggest bill comes from … electricity providers! Data servers running at full capacity consume a lot of energy. This makes data strategy a pressing issue. 

E-commerce

The more information you can catch and track about your buyers’ behavior, the bigger headache your data storage becomes. Apart from this, making sense out of all the data you have ever saved requires a stable data solution. 

Automotive

This section should be called machine learning or artificial intelligence. In fact, the automotive industry is one of the few that have taken it seriously. To train autonomous cars’ intelligences, manufacturers keep accumulating visual data in enormous amounts.

Cryptocurrencies

The financial industry was a silent pioneer of big data: credit card fraud, credit scoring, etc. have been developed decades ago. Nowadays, cryptocurrencies, such as bitcoins, took their turn in generating mountains of data that wait to be analyzed. 

Stock markets

Other veterans of the big data scene. Each iteration on the stock market is tracked, and there are billions of them happening during a day on the most famous ones like NASDAQ. Someone has to take care of all this data to make it re-usable for forecasting. 

Want to make a data science career? You know which kind of company you should be looking for 😉

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