Big Data In Industry 4.0 has long ceased to be a distant term with a futuristic meaning and has become a reality in the Industry. The 4th Industrial Revolution has several tools and technologies: the Internet of Things (IoT), machine learning, robots, and artificial intelligence. However, there is a basis for all this to be possible: Big Data.
Big Data is the name given to any significant volume of data needing specific tools and technologies to be collected, treated, and analyzed correctly. All this quickly and efficiently! That’s why Big Data in Industry is so essential.
With this technology, a factory can, for example, collect data from all machines, robots, operators, and commercial transactions with retail and sales and transform them into valuable information. This allows a detailed analysis of the entire production chain of the Industry and directly impacts the company’s management, decision-making, and functioning as a whole of the sector.
And the Industry in the world is already looking at the benefits of Big Data: 35% of the companies that already operate in the industry model 4.0 expect gains above 20% in the next five years, and 72% of this sector see Big Data and in data analysis a great potential to improve customer relations! If it was unimaginable to obtain data of various types at the beginning of the Industry, today it is almost impossible to measure everything that can be extracted and the value generated through them.
How To Start Applying Big Data In Industry
To work best with Big Data, it is necessary to guarantee some things beforehand. To collect the data correctly, there is a crucial data preparation step. This means cleaning, normalizing, combining, and organizing the data to be analyzed. This phase is essential for a successful Big Data application.
After this process, data mining – or data mining – takes place. It is at this stage that, with the prepared data, the search for patterns or anomalies that can generate insights for the Industry begins.
At a more advanced stage, technologies such as machine learning come in to make decision-making more intelligent, grounded, and automated.
Benefits Of Big Data In The Industry
Big Data in Industry mainly allows for transforming data into information to optimize products and services provided. What was previously wasted due to a lack of trained professionals (such as data scientists and engineers), and collection and analysis structures can now be used from end to end in the sector.
This tool allows understanding the past, identifying planning errors; generating possibilities for analysis of what happens today inside and outside the company; and it also makes it possible to look with more certainty into the future of the business, anticipating mistakes and predicting consumer behavior.
What does this mean in practice? Decreased errors in production, cost reduction, operations with better performance, more informed strategic planning by managers, and creation of predictive systems for machine maintenance. These are just some examples of the possibilities of Big Data in Industry.
The 5 Vs. Of Big Data
Even unconsciously, the use of Big Data in Industry is relatively recent. After all, it is an industry that has always generated a large amount of data. But it was only in 2001, in an article published by researcher Doug Laney that the concept spread.
In that same article, Laney presents the 3Vs of Big Data – which today have become 5. These pillars indicate whether the problem observed in the Industry needs to be addressed with Big Data technology. They are volume, velocity, variety, integrity, and value. Let’s understand each one of them:
Big Data deals with a large volume of data, measured in terabytes or even zettabytes! Imagine a company like Facebook, for example. Every day data is generated from more than 10 billion messages, almost 5 billion likes, and 350 million images. In Industry, it is no different. Even the turbine of a Boeing or an Airbus generates millions of data! With a good analysis of these, the ample volume is a plus!
Today data is generated not only in large amounts but at a very high speed. The analysis needed to make decisions needs to keep up with the pace at which data is generated, and this is a scenario of Big Data in the Industry.
This pillar talks about the various formats in which data can be presented. If in Industry, you work with financial transactions, sales, and presence in social media, in addition to the work of operators and machines, then we are talking about Big Data.
We have already seen that data is generated in incredible volume and speed, right? Because of this, you need to ensure that this data is still authentic and accurate when it is collected and used for analysis.
Big Data in Industry is an investment; therefore, it is essential to establish a clear objective of what is expected from these analyses. It is a complex job with great potential for positive results for companies. Therefore, evaluating the cost x benefit of the operation is also extremely important.