5 Industries That Rock Big Data Analytics

5 Industries That Rock Big Data Analytics

  • 10/2/2019

Each day we produce 2.5 EB of data. This is 2.5 billion gigabytes of information about everything. This creates unlimited opportunities for collecting, processing, and analyzing vast amounts of both structured and unstructured data, also known as Big Data.

How can any business benefit from the proper use of BD? 96.1% out of Forbes 1,000 list report growing investment in Big Data and AI. Among the top reasons are the need to be agile and fear of disruption.
We have noticed that some industries pioneered the process and now are using Big Data for their advantage more than the others.

Finance, banking, and Big Data

Financial systems are complex on their own, so they demand sophisticated decisions to gain a competitive advantage. Big Data has numerous applications in finance and banking: advanced decision making (to expedite the process and have real-time information), process management (to analyze response time and delays), customer’ profiling (to create accurate segmentation, forecast the needs, deliver personalized services), or even fraud and risk management (to analyze previous cases and reduce the potential exposure).

Example: JPMorgan Chase is using big data analysis to establish acceptable prices for properties that have been repossessed and minimize the risks of local property market default. That helps the company to establish price ranges more accurately and reduce the risks of failed mortgages.

Big Data analytics in transportation & aviation

Another industry that has a lot of data to collect, store and the process is transportation. Regardless of the size or type of vehicles, this industry leverages Big Data analytics to schedule maintenance and repairs, estimate the volume of passenger traffic, forecast delays, or even reduce the emissions.

In this case, Big Data helps not only deal with the tasks at hand but also make predictions about the growth of the networks or even help calculate a long-term demand.

Example: GoGo, a North American in-flight connectivity provider, invested heavily in Big Data adoption, built the BD warehouse and cloud-based platform and extracts BI reports from the data. As a result, an outsourcing vendor has built a direct big data analytics pipeline.

Healthcare and Big Data adoption

One of the industries that ride the Big Data wave is a medical and healthcare industry. 2019 Big Data and AI Executive Survey Reports say that the number of companies that heavily invest in Big Data has doubled compared to 2018 (8.8% and 16.6% respectively).

The practical applications of Big Data are numerous: the use of  Electronic Health Records (EHRs) to oversee medical research, make predictions and
better-informed decisions, and much more. Hospitals can keep track of their patients, offer more personalized assistance, or even prevent the abuse of some medication.

Example: Four public hospitals in Paris are using ten years’ worth of
records to predict daily and even hourly numbers of expected patients. The system was designed to be easily scalable and distributed among all the 44 hospitals if proved successful.

Big Data analytics in telecommunications

Telecom relies heavily on Big Data and insights it provides. With the largest number of connected devices than ever before, telecom companies need to рфтвду the growing amounts of data they receive. A lot of firms cooperate with big data analytics consulting companies to treat the stored data properly.

Such companies use Big Data to improve customer experience and provide better recommendations, reduce service time, predict network capacity and demand, and reduce customer churn. It can also be used to improve security or even collect feedback about new products much faster than before.

Example: Lebara, one of Europe’s fastest-growing mobile virtual network operators (MVNO), decided that outsourcing big data and overall digital transformation is a great choice. The company managed to improve the overall quality of the services as well as introduced several new products. 

Retail & eCommerce

Personalized customer experiences are what powers the modern-day sales. Whether we are talking about in-store sales or e-commerce, Big Data can improve the sales process significantly. The companies within this industry use analytics to gain insights from buyers’ journeys, increase conversion via personalized assistance and promotions, as well as gather information from multiple points of sale and predict the behavior of potential clients.

Moreover, operational management is another huge benefit. Many companies optimize their staffing procedures, carry out inventory analysis, or even predict the need for maintenance. 

Example: Target, a large US retailer, uses Big Data not only to offer personalized ads and promotional goods but also to track how shopping habits change. A few years back, this chain tasked their data scientists with a challenge to find a way to single out a potential segment, track, and target specific customers.


It might seem like the world becomes a place where data rules. Unfortunately, only 31.0% of all companies say they are data-driven. Even now, with the exemplary success of many companies across various domains, others still doubt.

However, it seems like the wide-spread adoption of big data is inevitable. The times when the guessing game was the only ground for decision-making is over.

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