How Big Data Is Shaping The Future Of All Industries

Infinite volume, real-time and unstructured formats characterize Big Data, and these elements will redefine the future of business and industry. The uses of Big Data are endless, but some significant areas emerge. Big data is often presented as the new Eldorado. In a somewhat unfavorable national economic context, it is perceived as a miracle cure, which could allow companies to create value and gain a competitive advantage.

But beyond the buzz, is there a real’ big data’? And how can this phenomenon redefine the operation and the very nature of companies?

Being able to process, store and analyze these vast and continuous data flow offers an infinity of new possibilities to support decision-making, to acquire knowledge, to optimize activities and to innovate.

Organizations that can transform this data into strategic information will have a decisive economic and strategic advantage. Here is how big data is shaping the future of all industries.

  • Improve production and decision making. More and more factories are betting on Big Data to be more competitive. Also, all this information improves decision-making and, above all, the decentralized one. The person who needs it has access to the analyzed data to decide knowing all the variables.
  • Improve the relationship and contact with the client. Knowing the consumer is key to any business. Through Big Data analysis, you can personalize your experience, analyze your motivations, give you better assistance or reinforce your retention. The Kroger supermarket chain has used Big Data to customize its marketing campaigns, achieving a 70% return rate.
  • Increase the competitiveness of traditional industries. Sectors that are considered less innovative, such as agriculture, are also applying the Big Data analysis to be more competitive.


Big data is a general awareness of the amount of data that is now available to businesses and other organizations, and the potential they contain as well as the strategic opportunities that can be generated by their treatment. As a result of this awareness, there is a change in the way companies operate and a redistribution of competitiveness cards.

New technologies and companies have grown in the heat of Big Data. The data is the gasoline of artificial intelligence, which is, in fact, the great goal shortly for most companies that use Big Data. Artificial intelligence will be able to do everything we’ve seen and will do it automatically, with little or no human supervision. Companies will depend on different ways to manage their data with applications using JD Edwards and other tools, and these applications will open possibilities for growth and efficiencies in the future.


In the automotive sector, machine learning combined with the ever-increasing computing power makes it possible to identify, in real time, any obstacles that arise on the road, an essential skill for developing autonomous vehicles. This technology also allows for predictive maintenance of cars and other trucks to minimize accidents.


In the world of the industry too, machine learning makes it possible to adjust the maintenance schedule according to the data collected directly on the equipment, to avoid as much as possible the breakdowns and the significant loss of revenue that they generate for the company. Data analysis also helps to optimize the complex production cycles of some plants.

Consumer Goods 

By dissecting the data collected in stores on the behavior of the consumers, the big surfaces can, thanks to the automatic learning, reorganize their departments to boost their sales. Machine learning also gives distributors the opportunity to optimize the management of their stocks.


In finance, this technology makes it possible to track fraudulent transactions by sifting through the bank data of buyers, but also to offer them ultra-personalized financial products, by compiling information collected via different channels.


Through machine learning, farmers are starting to customize their growing techniques based on weather data and the unique characteristics of a given portion of their land. The goal: to produce more by polluting less.


Using sensors on their infrastructure and machine learning technologies to process the collected data, energy providers can predict in advance when their wind turbines (for example) may fail and send a maintenance agent upstream.


As shown in the table below, which analyzes the impact of machine learning on the world of fitness, some software is able to diagnose a disease by examining the results of a scanner, a biopsy or other types of medical tests.


In the pharmaceutical sector, this branch of AI can optimize clinical trials by selecting patients more appropriately. Laboratories will also be able to maximize their product launch strategies by combining a large number of market data with the results of previous marketing operations.

The Public Sector 

Optimizing the allocation of resources for a harmonious urban development that maximizes the quality of life, improving public policy decisions through the analysis of large datasets … The state also has advantages to be gained from the use of the machine learning.

Media Production & Entertainment 

With this technology, the press can compile data from different sources about their audience and offer their advertisers more personalized and therefore more lucrative advertising space.


Telcoms will be able to optimize the hefty investments that they must make to maintain their infrastructure by analyzing the data collected in the field by sensors. The machine learning will also allow them to create intelligent voice assistants, able to handle the majority of calls that are now managed by the employees of their call centers.

Transport, Logistics, Travel 

Machine learning enables transport stakeholders to optimize their pricing through real-time demand analysis, as shown in the graph below. In the world of travel, this software allows tour operators to offer tourists ultra-personalized offers.

Also, in this way towards the intelligent management of massive data, many actors have appeared reinforced. From historical international giants, such as IBM or Microsoft, to new companies, although the implementation of Big Data techniques goes somewhat slower.

Big Data extends beyond new and traditional industries, large companies and small businesses, technologies and processes. Big Data is a way of understanding (and taking advantage of) the hyperconnected world we are creating.



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