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With the advancement of technology, companies must take into account the big data challenges posed by Industry 4.0. The goal for companies to achieve Industry 4.0 is simple: to maximize efficiency and profits, operate more efficiently, and introduce automation technologies in areas that are dangerous or repetitive wherever possible. With the advancement of technology, companies must take into account the big data challenges posed by Industry 4.0. The goal for companies to achieve Industry 4.0 is simple: to maximize efficiency and profits, operate more efficiently, and introduce automation technologies in areas that are dangerous or repetitive wherever possible. To accomplish these tasks, financial and human resources support are needed, as well as meaningful operational information. In other words, it requires big data. Any company that wishes to reap the benefits of Industry 4.0 must first address some of the following big data challenges: 1. Isolated data. The lack of cross-platform, cross-departmental data sharing is likely the biggest obstacle for companies aiming to implement Industry 4.0. Company data existing on “islands” may benefit a certain party or department, but it usually leads to waste. True business intelligence cannot be achieved if each department in an organization cannot share data and insights with one another. For example, in the operations of a semiconductor manufacturer, this company ends the \"data loop\" by sending data back from the testing stage of production and seamlessly \"integrating\" it into the early stages of development. This allows the company to detect defective products early and improve its quality overall. 2. Data system redundancy Another issue closely related to isolated data is data system redundancy. Some companies may use Enterprise Resource Planning (ERP) systems to track various aspects of their business, including customers and suppliers. But what if a company has more than one enterprise resource planning system (for example, one for each facility or sales region) and needs to transfer data between them? What if there are 30 such systems? This is the problem faced by Anheuser-Busch InBev, as the company merged several of its subsidiaries and became one of the most well-known companies in the global beer industry. The company had 27 different enterprise resource planning systems at that time. Now, they use only one enterprise resource planning system in order to make better use of data analysis, reporting, and other digital tools, which benefit from a centralized and organized enterprise data repository. Pressure transmitters: yunrun.com.cn/product/ 3. Talent shortage: Many companies are competing to hire data experts to help establish and maintain databases, so as to extract insights from the data available in all organizations (or to develop tools for collecting such data). This raises a problem: many companies are recruiting employees at the same time. American companies currently need to hire over 150,000 data scientists. This is based on a survey conducted by LinkedIn among American companies, and these positions are still in short supply to this day. Another challenge closely related to staffing is the shortage of skills among applicants. These include some skills that are difficult to master, such as mathematics and software development. However, excellent data scientists also need to possess many soft skills, such as good communication abilities and the skill to tell others the stories they can see in the data. 4. Security and Data Access Nowadays, there are many articles on security vulnerabilities in the Internet of Things (including industrial machine control devices). Throughout the business landscape, decision-makers remain reluctant to invest in the Internet of Things and other digital transformation technologies due to concerns over the security issues posed by such assets. In fact, according to surveys conducted by Forrester and ForeScout, around 77% of companies say they are now facing some “significant” security challenges that they didn’t have to worry about before. But what are these challenges? How can businesses address them? Here are some solutions: • Connected industrial devices, including sensors, trackers, and control devices, do not always have strong security features. Enterprise employees must be familiar with the update process to ensure that remote devices receive security patches regularly. •Data access within enterprises that follow a digital-first approach represents another serious issue in data security. Companies must implement appropriate authentication procedures to ensure that employees can only access the databases for which they have permission. •Physical security in modern warehouses and manufacturing plants is also an important issue. The correct logging procedure must always be used to keep the server cabinets locked and under surveillance, in order to ensure the security of the company’s valuable servers and analysis equipment. When it comes to data security and the ability to access data, many details can attract people’s attention. If a company enters into a contract with an external firm to use its data facilities, certain issues need to be addressed, such as the capability of that firm’s data center for security protection. Companies always need to weigh the pros and cons when deciding whether to establish an internal data infrastructure or rely on third-party infrastructure. However, in both experiences, certain challenges (such as unforeseen plans) are the same. 5. Lack of identity and compatibility. Finally, another challenge is how to ensure the acquisition. It is undeniable that the widespread adoption of Industry 4.0 can increase productivity in various sectors across the United States—such as transportation, energy transmission, healthcare, and manufacturing—by 35%. But at the same time, companies may have both old and new systems, which do not always work well together. Today, disruptive digital technologies have opened new doors for businesses, but they also increase the risks associated with complex supply chains. Just as various departments within a company need the right digital tools to ensure smooth data flow, companies also need to be able to exchange records, authenticate users, send notifications, and more in real time and seamlessly. As long as these challenges are kept in mind and investments are made in the right people, creative ways can be found to overcome them. Big data and Industry 4.0 hold great potential in terms of production and profits. Although they may seem complex and difficult to address at present, there will always be a way to solve them in the future.