How Big Data and IA work together

Big Data and AI are two of the technologies that are marking where the world of the future is heading, which will undoubtedly be a place dominated by data and information.

The amount of data generated in the digital world has been growing exponentially for years. The World Economic Forum has already predicted that the amount of data in “the digital universe” is expected to reach 44 zettabytes by 2020. It is this information that will mobilize the social, political and economic decisions of the future, in a process that has already been adopted by many organizations. Thus, Big Data and AI will be the two technologies needed to draw conclusions

These are two systems that generally work together, so that the artificial intelligence feeds on the stored data and uses it for Big Data analysis, achieving the improvements and optimizations that these technologies allow.

Big Data and Ia: what they are and how they are transforming the world

Big Data and AI are two closely related technologies that, together, allow the optimization of processes and decision making.

The Big Data, often translated into Spanish as macrodata, refers to huge and complex sets of information. Because of their size, they require fast processing applications and computer technologies. In itself, the Big Data is also that large amounts of data, the ability to exploit them or, draw conclusions that give value to the business.
The characteristics that define the Big Data are volume, speed, variety, truthfulness and value.

Big Data analysis allows organizations to discover hidden patterns, unknown correlations and all the stored information useful to make better decisions in a more efficient way. In this way, data scientists and other users access information that allows them to anticipate trends or prevent problems.

Some examples of how Big Data analysis is being applied:

  • In industries, optimizing the performance of machines and devices. Big data analysis is helping machines and devices to become more efficient, intelligent and autonomous.
  • Process improvement in companies is becoming ubiquitous and transversal in many different industries. As an example, Big Data analysis is enabling optimization of supply chains or shipping routes, taking into account information on trends in web searches, social networks, data on actual buyers and even weather forecasts.

It is also common to apply this analysis in the maintenance of machinery in a predictive way. Platforms like Nexus Integra appear to make the power of Big Data available for process optimization in the context of large industrial assets.

  • In the medical field, Big Data analysis is already enabling improvements in disease prevention by allowing data to be collated at levels never before imagined.

Intimately linked to the analysis of Big Data is artificial intelligence, which in turn includes many other diverse applications. A machine that applies AI is one that discerns information about its environment and acts on that information to successfully accomplish its tasks. In other words, artificial intelligence implies that machines carry out processes for which only human cognitive ability was hitherto believed to be suitable.

One step further is the application of machine learning, a branch of artificial intelligence in which technologies are designed that are capable of automatic learning from the patterns that are identified among the macro data.

In this way, machine learning means the automatic learning of the machines and the continuous and automatic improvement of all the processes entrusted to them, based on trial/error mechanisms.

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How Big Data and AI combine

By applying both technologies simultaneously, Big Data and AI enhance the possibilities of each. The main applications appear in the world of business and industry, where artificial intelligence is already providing access to predictive and relevant knowledge for decision making.

Simply put, Big Data is only useful if the artificial intelligence tools appear that are capable of giving it meaning and extracting valuable information from that huge amount of data. The Big Data is therefore the engine and the basis on which artificial intelligence and machine learning are nourished and makes it possible for these systems to be able to identify complex patterns in millions of data and predict future behaviour.

In order to reach profitable conclusions, from the large amount of data generated by the control and monitoring elements (sensors, PLC, SCADA) and databases, it will be vital to ensure that the data obtained by the organization is also valuable. These data are dispersed and not standardized, so it is key to have a platform capable of integrating data from different sources, so that they can be unified and stored as easily as possible and can later be visualized and exploited.

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The benefits of merging Big Data and IA

Companies all over the world and of all sizes are combining Big Data and AI to achieve competitive advantages.

Some of the applications of combining Big Data and AI include:

  • Improvement in customer services. Increasingly, and thanks to the power of combining Big Data and AI, businesses are understanding what their customers are looking for in order to provide it.  McKinsey’s report: Jobs lost, jobs gained: Workforce transitions in a time of automation, already advanced that the attention to the public is one of the professional categories with less potential to be automated. However, the digital transformation will free employees from certain repetitive and automatic tasks, freeing them to spend more time on interpersonal communication.
  • The drive for optimization in industry and business. The combination of Big Data and AI brings with it the power of prediction. While until now business decision making has often involved human error, Big Data’s artificial intelligence and analysis will transform many industries by enabling anticipation and improving efficiency.

Automation and the use of Big Data and AI involve an initial investment by companies. However, in the medium and long term it allows them to cut down on unnecessary costs and expenses.

Among the advantages of these systems are predictive models capable of predicting and correcting anomalies in the production process in real time before failures occur. In this way they help to maximize machine uptime, production and minimize errors. All this translates into a reduction of the unit cost.

In this sense, platforms such as Nexus Integra are already allowing the application of Big Data and IA in an industry environment. Allowing the acquisition of any data and offering a structured Big Data platform that facilitates the application of AI and Machine Learning to data scientists, as well as the exploitation of the data in any of their native or external applications. Nexus Integra as an integral operation center and Big Data platform allows giving value to the data.

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