In connection with ScaleUp 360° Industry of Things, the German speaking digital event for strategists and thought leaders in smart manufacturing & process optimization, we.CONECT Global Leaders interviewed Arjan van Staveren (Country Manager Germany) from Snowflake about their participation at Industry of Things.
INTERVIEW-PARTNER
Arjan van Staveren, Snowflake Inc. & Barbara Duna, we.CONECT Global Leaders GmbH
we.CONECT: Why is data quality so important for valid analyses?
Arjan van Staveren: Data analyses are a central building block when it comes to setting companies apart from the competition and securing their own success in the long term. It not only helps them to identify potential weaknesses, to better understand their customers and to improve products and services, but can also open their eyes to previously undreamed-of potential. For this to work in practice, however, it is not only the quantity of data that counts. If its quality is inferior, even the most advanced technologies fed with it will not produce useful results. So companies should definitely not confuse quantity and quality. Even if there is an enormous amount of information, it may not be complete or it may be in the wrong format, which is why it can quickly skew in one direction or the other. In the worst case, this leads to poor data resulting in poor decisions.
Raising awareness for this is the first important step. In order to permanently solve the problem of data quality, companies should, on the one hand, rely on a platform that brings all information together and thus prevents a certain area from being forgotten, the insights of which could turn out to be crucial. On the other hand, it is important to establish uniform data governance rules that apply to all departments. This not only ensures who has access to what information and to what extent it can be used. It also regulates that all data generated internally or flowing in from different sources have the same quality standards and can be used for analyses that are guaranteed to produce valid results.
Raising awareness for this is the first important step. In order to permanently solve the problem of data quality, companies should, on the one hand, rely on a platform that brings all information together and thus prevents a certain area from being forgotten, the insights of which could turn out to be crucial. On the other hand, it is important to establish uniform data governance rules that apply to all departments. This not only ensures who has access to what information and to what extent it can be used. It also regulates that all data generated internally or flowing in from different sources have the same quality standards and can be used for analyses that are guaranteed to produce valid results.
we.CONECT: What challenges does the manufacturing industry face in the area of data storage and processing?
Arjan van Staveren: Legacy systems, which have grown historically, are still a major problem for manufacturing companies in particular. They have led to information being trapped in silos separate from each other. How large the amount of data is exactly, where which information can be found and whether there are any duplications can hardly be kept track of in this outdated scenario. Using it for analyses is therefore still a major feat for many companies within the manufacturing industry – if not impossible.
To be able to change this in the long term, both a technological and a cultural change are needed. This means that, firstly, the necessary technological foundation must be laid that breaks down the existing silos and thus makes barrier-free data use possible. Secondly, it is just as important to create an awareness of the importance of data among all employees. Only when everyone is working together will companies be able to ensure that no new silos are created and that all available information is always maintained to the best of their ability.
To be able to change this in the long term, both a technological and a cultural change are needed. This means that, firstly, the necessary technological foundation must be laid that breaks down the existing silos and thus makes barrier-free data use possible. Secondly, it is just as important to create an awareness of the importance of data among all employees. Only when everyone is working together will companies be able to ensure that no new silos are created and that all available information is always maintained to the best of their ability.
we.CONECT: How is Snowflake’s Data Cloud Platform changing the IoT landscape?
Arjan van Staveren: For IoT devices to work and add real value, a barrier-free flow of data is essential. Ideally, this should take place in near real time – both in the cloud and in combination with on-premise solutions. Imagine, for example, a networked production line that automatically lets you know when the next maintenance is due. Extremely practical in theory, but if this information does not reach the responsible department in time, production could come to a standstill in the worst case.
This is exactly where many companies still fail. They see the opportunities that the IoT landscape offers them, but they are not able to transmit them to live and make them accessible across all departments. This is where Snowflake’s Data Cloud can help. It forms the ideal interface for sharing IoT data without latency. Being able to seamlessly integrate data from on-premise solutions also plays an important role, as many companies still rely on hybrid structures. By combining the different systems, the collection and processing of IoT data is significantly accelerated. This gives companies the opportunity to identify optimisation potential and improve both internal and external processes, which will ultimately result in an increase in revenue.
This is exactly where many companies still fail. They see the opportunities that the IoT landscape offers them, but they are not able to transmit them to live and make them accessible across all departments. This is where Snowflake’s Data Cloud can help. It forms the ideal interface for sharing IoT data without latency. Being able to seamlessly integrate data from on-premise solutions also plays an important role, as many companies still rely on hybrid structures. By combining the different systems, the collection and processing of IoT data is significantly accelerated. This gives companies the opportunity to identify optimisation potential and improve both internal and external processes, which will ultimately result in an increase in revenue.
we.CONECT: Many companies have concerns about the privacy of their data. How do you ensure secure data sharing?
Arjan van Staveren: In order to be able to make data-based decisions, there is no way around it for companies to make their data usable not only internally across all departments. It also plays an important role in collaboration with customers, suppliers and other partners, and in some industries, such as government or banking, it is even mandatory that data be accessible to third parties. It is understandable that many companies are hesitant at this point due to security concerns. But there is a way to shatter these – and that is to share information, but not the actual data, with outsiders. This is where so-called data clean rooms come into play. They form a secure space that allows different actors to access and use data without being able to view or download it in detail. This way, the company providing it can ensure that no information is taken and used in a different context without consent.
we.CONECT: Looking ahead, what topics and trends regarding the smart factory do you see in the next few years?
Arjan van Staveren: There are many trends and it will certainly take a while before the technological foundation is laid to turn them from theory into practice. Especially in the smart factory sector, the data mesh could play an increasingly important role as an alternative to a centrally controlled IT infrastructure. It is often said that there is no way around this on the road to success. However, due to its domain orientation, the data mesh could offer companies precisely the technical insights that are often lost with a central system. As each domain has its own data team, typical bottlenecks can be avoided and new data sources can be integrated more quickly. It is important that both the quality and the interoperability are uniformly regulated for all domains so that the information can always be used across the board. In this way, silo formation can be avoided even without a central IT infrastructure. At the same time, the individual data teams have the necessary expertise that is important in their respective domains. In this way, they not only ensure agility in a constantly evolving ecosystem, but can also identify and remedy emerging vulnerabilities more quickly.
we.CONECT: Thank you very much for the Interview!
YOU WANT TO KNOW MORE ABOUT THAT TOPIC?
Attend our ScaleUp 360° Industry of Things, the digital event about Industrial IoT for the German speaking community.
