Industrial data is currently going through its fourth transformation phase, with a focus on automation, IoT/IIoT solutions, CPS (Cyber-Physical Systems) implementations, cloud services, and AI.
At the center of industry are the collection of data and its utilization in various systems and processes, such as predictive maintenance optimization, operational efficiency, production assurance, and the collection of production data combined with customer data. Additionally, there are other potential targets for the use of advanced analytics, and we will undoubtedly see many new innovations in the industry in the future.
The development of data utilization is still challenging, as advanced analytics models require reliable and well-organized data. Especially now, as technology continues to rapidly advance through LLM implementations (such as ChatGPT/OpenAI) towards the Industry 5.0 era, companies should be aware of the risks associated with these new development trends.
Data Management Maturity and Its Impact on Utilizing New Technologies in Decision-Making
The importance of securing information and data-driven decision-making has been discussed in the industry for years. However, companies' ability to utilize new technologies may not always keep up with the pace of development. The ability to utilize new data-driven technologies depends heavily on how mature a company's data management processes are and how precise its understanding of its data assets is.
To support rapid experimentation, it is essential to establish clear rules for how companies can use their data with new technologies. Clear data classification and ownership, as well as a functional governance model, are essential for this. The data owner is responsible for defining the permissible and licensed data utilization models. This way, companies can respond to new technologies and opportunities in a sensible way while protecting their business.
With the above measures, companies can also begin to build continuous cybersecurity for their data assets, especially considering the constantly evolving cyber threats.
Protecting Sensitive Data in Industrial Companies
The data managed by industrial companies is vital for their operations, and any unauthorized access or manipulation can result in severe harm to the company and its customers.
To ensure data protection, the company must first identify what needs to be safeguarded. Establishing a classification, ownership, and governance model becomes essential in constructing effective protection mechanisms. These pillars serve as crucial support in implementing sensible data protection measures.
In large enterprise environments, it is recommended to utilize a dedicated metadata management tool for handling the mentioned tasks effectively. These tools facilitate the implementation of classification, ownership, and governance practices. An added advantage is the ability to leverage automation, which enhances the efficiency of these tasks.
By utilizing metadata management tools, companies can strengthen their cybersecurity measures and better protect their valuable data assets. At CGI, we have successfully implemented tools and solutions following this approach for our larger customers. With our expertise, we can assist customers in finding the most suitable solution for their specific environment.
Cybersecurity protects the seamless cooperation between business, IT, and data
Data-driven management relies on the company’s ability to understand, manage and utilize data at the right time in the right place. This is achieved with mature data governance abilities, which also include cybersecurity as an integral component of data management. It is also recommended to have a strategic approach to the company’s data usage, which defines the priorities, goals, and limitations of how to use the company’s data assets in a secure way to develop new innovations.
With the emergence of new technologies and innovations, the scope of threats faced by businesses is expanding. Hence, proactive anticipation and planning for these threats become crucial to foster sustainable and profitable growth. Security plays a vital role in enabling businesses to effectively leverage data.
Investing in proactive cybersecurity is valuable as preventive measures are cost-effective and easy to implement. Collaboration between business, IT, and data happens seamlessly when data is guiding business decisions, IT is making strategic technology investments, and security is protecting data for the future.