There is a lot of discussion about this tool and its functionality in the business world, and if you work with technology, Big Data is part of your daily routine. But in practice, how does this tool work and what role does it play in Industry 4.0 solutions? Keep reading to learn more.
The concept of large volumes of data
Big Data is a term that describes the large volume of data that passes through a company every day. This data can be analyzed for insights that lead to better decisions and strategic business moves.
So what matters is not how much data there is, but what the company does with it.
Today, a major challenge faced by companies is precisely processing the growing amount of content and mapping its behavior, trends and business opportunities.
Big Data comes to these companies as a solution. The tool, which is able to combine large volumes of data with analytical intelligence, can store and work with a lot of data, generating accurate insights for companies.
But what exactly is Big Data?
The concept is not very old, originating in the 1960s and 1970s, when the first databases were built in the United States.
In 2001, Gartner, an American consulting company that develops technologies related to customer insight to support decision-making, created the definition of Big Data that is accepted to this day:
“Big Data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation”.
In practice, the tool began to become more common in 2005, when online services such as Facebook and YouTube saw the amount of data they were generating and needed to put it to work in their favor.
The large volume of data that Big Data refers to can relate to any amount of information from a company or a specific subject, because what matters is that the data in this aggregate is accessible.
It does not matter whether it is structured (spreadsheets, tables) or unstructured (images, blocks of text), or where it is generated. After all, diverse data can make up Big Data, from your inventory control information to customer browsing data in your business's app, for example.
Whether numbers, names, access history, usage maps or geographic data, everything can be organized in a database.
Does every company have Big Data?
Yes, but there is some confusion about this.
The more digitalized a business is, the more data it will have available in its Big Data. Multiplying this data is a mission that depends on the modernization of the company and also of its products.
A company that makes bicycles, for example, will not have the same volume of data as a company that develops software.
However, the bicycle company will have other sources to draw on, such as its support, quality control and customer satisfaction surveys.
The volume of data, therefore, will depend on the tools the company has for collecting, storing and processing that data.
What is Big Data for?
Big Data has the capacity to reshape business models, products and management strategies. The tool can be seen both as a technology resource and as a means of advancing companies toward competitive advantage, since its main function is to generate value for them.
The functionality allows companies to organize, read and interpret qualified data about everything related to their process or their product/service.
Thus, Big Data works by improving companies' management strategies through data analysis, assertively supporting issues at the critical points of their business.
The overall impact of large databases ranges from a failure that can be traced to the root of the problem to a future trend that can be incorporated into products. The technology thus generates overall returns from HR to the shop floor, and can be used equally in all sectors of the market.
How does Big Data work?
Before starting to use data, it is necessary to understand how this information structure works within a company. In general, there are a few steps to follow, such as:
- Define a Big Data strategy
- Identify Big Data sources
- Access, manage and store the data
- Analyze the data
- Make data-driven decisions.
These tasks can be applied across three main areas: integrating, managing and analyzing data.
Integrate
A Big Data strategy aims to help your company oversee and improve the way data is acquired, stored, managed, shared and used inside and outside your organization.
Therefore, when developing a strategy, it is important to consider existing and future business and technology goals and initiatives. This requires that the handling of Big Data be an important part of the company's strategic planning.
But for this planning to work, it is necessary to know the company's data sources, which can be:
Internet of Things (IoT) and other smart devices that feed IT systems, such as wearables, smart cars, medical devices, industrial equipment and more.
Social media, such as Facebook, YouTube and Instagram. This includes large amounts of big data in the form of images, videos, voice, text and sound, and is useful for marketing, sales and support functions.
Management systems, such as ERPs, CRMs and other types of service platforms specialized in managing parts, departments or the business as a whole.
Manage
Modern computing systems provide the speed, power and flexibility needed to quickly access large amounts and types of information.
But in addition, companies also need methods to integrate data in order to ensure the quality of the analysis.
That is why management systems serve to bridge departments, devices and equipment, centralizing business data.
Storage depends on the company's conditions and objectives. One current trend is companies betting on cloud solutions because of their scalability and resource savings.
Analyze
With enabling technologies in their businesses, organizations can analyze data and determine in advance which data is relevant before analyzing it.
From there, Big Data analysis is how companies gain value and insight from the data they hold, and it is up to them to make intelligent decisions based on the insights from that data.
To remain competitive, companies need to make the best use of Big Data capabilities and be guided by their data, deciding based on the evidence it presents.
5 applications of Big Data in Industry 4.0
To demonstrate the importance of Big Data solutions, we have selected some of their main uses in companies. Check them out!
Predictive maintenance
With Big Data, companies can collect real-time data from the machinery used in production.
This makes it possible to detect potential failures before they occur, reducing machine downtime and increasing production efficiency.
Process optimization
Big Data makes it possible to analyze large volumes of data and identify production patterns and optimization points.
Based on this information, companies can implement improvements across the entire production process, increasing efficiency and reducing costs.
Risk analysis
Risk analysis is an essential tool for companies operating in sectors with a high risk of accidents, such as the chemical and petrochemical industries.
With Big Data, companies can collect information on machine behavior, pollution levels, temperature and other parameters that may pose risks to workers and the environment.
Quality control
With the use of sensors and other technologies, industry can monitor the quality of the products it produces in real time.
With Big Data, this information can be collected and analyzed in real time, allowing those responsible for quality control to make quick decisions about nonconforming products and reduce the risk of rework.
Production personalization
With Big Data, companies can collect information about customer preferences and identify consumption trends.
This information can be used to personalize production, better meeting market needs and increasing customer satisfaction.
Enacom has been in the market since 2009 developing innovative solutions that deliver better performance and are operationally more predictable and profitable.
Big Data is one of the technologies most used in our software to ensure efficient optimization across many segments. Talk to our experts and develop solutions using Big Data with Enacom.
Learn more: explore the Performance Digital Twin.