The term big data continues to gain popularity: examples of use in different areas of business and markets are growing more and more. We can practically find it anywhere: every time we activate the random mode of our Deezer account, or when we use Google Maps, or when we order an Uber, there is big data behind it.
In this article, we have compiled some examples of the use of big data in business, where its implementation has allowed the correct analysis of large amounts of information and, consequently, better decision-making. Join us!
Get to know these 8 examples of the use of big data in business
1. Big data for mobility in the city
Little by little, GPS data, the location of key points in a city, real-time monitoring of public or private transport units, weather conditions, and CO 2 emissions, among others, help to create a network of information to plan and optimize the mobility of its inhabitants.
This not only provides valuable data on the planning of a street or neighbourhood but also warns about some shortcomings that are not always taken into consideration, such as access ramps on buses, subway stations or sidewalks, efficient signage for people with problems with vision or literacy, etc.
If analyzed properly, it is possible to create opportunities to design the city efficiently and include suppliers that meet these needs (producers of means of transport, for example). In London, it is already being implemented to make predictions about demand at peak times, establish individual mobility patterns & understand the impact that the use of autonomous vehicles would have as part of the transport offer.
2. Big data in health
For the production of new vaccines or medicines, a great deal of research is needed, from the disease that is to be alleviated or prevented to the performance of the drugs being tested. Thanks to big data, it has been possible to process more efficiently, for example, the development of vaccines for COVID-19: their effectiveness, their weaknesses and their side effects.
Thanks to this, it is not only possible to have a cure in less time, but there is also a greater variety of offers from different laboratories; this allows to increase production, purchase of doses and shipment to different countries and markets.
3. Big data to guarantee sales
Amazon is a giant: we all know it. And that’s why it does so much more than create shopping recommendations for Prime members. The company wants the buying odds to always be in its favour. That is why it pays attention to what people consume in its streaming application, the purchase history, what they have already searched for, the information on products that (although they did not buy) have similarities with other articles, the offers that were opened from their emails electronics and more.
So it’s no coincidence that you first see discounts on cycling accessories if you bought a bike a couple of days ago. You have to equip it to travel safely, and Amazon knows that .
4. Big data in marketing
Netflix shows you options, according to your tastes. Have you noticed that there are different covers to introduce you to the same series or movie? In some cases, you will see the female protagonist, the villain or the mascot: all this is decided by the tastes of the users. Just as it is possible for it to show you a personalized list of recommendations, based on what you have already seen and rated, Netflix analyzes how to present you with content so that, from the image, it draws your attention.
What might draw you to the show Stranger Things: that there are teenage protagonists with romantic conflicts, that there are mysteries investigated by the police, or that it is set in the 1980s? Netflix will show you the door through which you will be encouraged to enter.
5. Big data in fraud prevention
Big data and data mining make it possible for the industry and financial institutions to prevent fraud related to the use of credit and debit cards. Nowadays, it is common to analyze the trends of a group of consumers in order to detect when there is any unusual activity.
This allows companies and entities to maintain the health of the economic system. Help customers keep their banking information and resources secure.
6. Big data in agriculture
Azucarera Española developed an application to make beet (or beatable) cultivation more efficient. With information such as sowing dates, the type of soil, the seeds used, temperature, climate, and frequency of rains, among others, it creates prediction models that indicate what can happen to the plot and what can damage or improve the tuber quality.
In addition, an estimate is made of the best dates for sowing or cultivation and the best substances are analyzed so that the production is optimal and kind to the environment, which translates into a follow-up that allows the hectares to be better used. to reduce costs and increase profits.
7. Big data in business insights
One of the best examples of the application of big data is the collection and generation of business information. Approximately 60% of the total data collected by businesses and social media platforms are not structured or analyzed by them. In fact, if this information is used properly, many of the issues related to revenue generation, customer satisfaction, and the development of new products and services can be solved.
Currently, as part of the digital transformation process, businesses have begun to adopt this technology to effectively manage and interpret the information they collect.
8. Big data in the banking sector
The amount of data generated within the banking sector has skyrocketed in the aftermath of the pandemic and is expected to grow 700% by the end of this year. The study of this information in the banking sector allows different illegal activities to be detected, such as, for example, the misuse of credit cards, money laundering, and the alteration of credit and risk profiles, among others.
Today there are different anti-money laundering software, such as SAS AML, which use data analysis to detect suspicious transactions.
There are many useful applications for big data in different industries and markets. It is only a matter of analyzing which data and tools are needed in each case. Do you already know which ones could become your new allies?