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The increase in data and processing speed have made Artificial Intelligence (AI) have the highest growth in history . And it is that the main base of this is the data, since it is nourished by them and uses them to obtain information from the environment, analyze it and act with it accordingly.
Fifteen years ago the mathematician and market researcher, Clive Humby , had expressed that “data is the new oil” , and he was not wrong. Since that time, and to date, the total amount of data in the world has multiplied by 74 .
It should be noted that with each interaction we make on a daily basis, we generate, transmit and receive data. These are precisely those that give us a current view of the status of a process or activity and, furthermore, those that allow us to predict results. For this reason, they are considered the most valuable resource today.
In recent years, Artificial Intelligence and Big Data have driven and generated a variety of technological innovations, which have shaped the current digital environment and Industry 4.0 . These two trends have a common goal: to get the most out of the large amount of data that is generated.
Aware of this reality, tech giants like Amazon , Microsoft, Netflix, among others, have developed a domain at the intersection, where Big Data meets AI. This convergence is what MIT Sloan Management Review has called “the most important development shaping the future of how companies drive the business value of their analytics and data capabilities .”
These organizations understand how to combine data insights and strong AI capabilities into differentiated solutions with massive market value.
From cataloging data to understanding it, Artificial Intelligence offers exciting new opportunities to manage large volumes of information . Some of them are:
Automation of data processing
AI and Deep Learning ( deep learning ) to automate all routine tasks related to data, such as integration and management. Data can be automatically sorted according to numerous parameters, eliminating the need to manually review it, as was done in traditional processes.
Information quality verification
In addition to processing all the data, Artificial Intelligence also allows checking quality problems or inconsistencies in them . This technology becomes an effective quality control system, with the aim that analytical and Big Data systems are capable of drawing reliable conclusions. When these problems are discovered, AI-based applications can automatically make corrections or flag these anomalies for the team to consider and take corrective action.
Artificial Intelligence and Big Data have driven and generated a variety of technological innovations / Image: Possessed Photography via Unsplash
Legacy data integration
There is still a large amount of information not digitized or in offline formats, stored on traditional management platforms. Advanced Artificial Intelligence technology makes it possible to rescue this data and make it accessible to current systems.
Development of rules for automated data management
Knowing which information to store and which to discard is a very recurring problem in the management tasks of any business, especially in those in which the volume of data is very extensive. AI helps make these decisions, analyzing data usage patterns and recommending optimal strategies for data management and storage.
As we can see, Big Data and Artificial Intelligence complement each other more and more. And it is that Big Data acts as an input that receives a massive set of data that needs to be processed and standardizes them to make them useful. Meanwhile, Artificial Intelligence is the consequence of this process. It consists of a set of softwares that take advantage of the output generated by these results to create series of algorithms that make programs and mechanisms can show intelligent behaviors and reason as humans do, giving rise to multiple advantages for companies .
In other words, Artificial Intelligence feeds on and learns from processed data, creating and recognizing patterns and developing sophisticated analytics solutions for all types of sectors.
Techniques such as machine learning, predictive analytics, and data visualization are the ones that help find meaning when digging into large data sets, and the ones that improve the speed and accuracy of decision-making.
Currently, all organizations with large volumes of information are adopting Artificial Intelligence as a key tool to manage their data. And it is that this technology will allow them to maximize the use and availability of data to predict scenarios, make decisions in real time and prevent failures.
For this reason, for any manager and company, it is increasingly important to understand the evolution of data to Machine Learning and Artificial Intelligence, as this will allow them to advance and grow within the emerging environment.