
How to drive trusted decisions without changing your current data infrastructure.
Learn more about DataOS in our white paper.
IBM states that 53% of manufacturing organizations leverage big data and analytics to generate competitive advantage. These organizations understand that an increasingly global and competitive landscape necessitates digital innovation and transformation. Big data is a key piece in staying at the industry forefront to better produce, maintain, and ship high-quality goods.
Leading manufacturers are already reaping the benefits of big data. Using big data analysis, the Coca-Cola Company was able to save ~$45M annually. Over two years, John Deere (Deere & Company) saved $900M in inventory control thanks to big data. These organizations demonstrate the huge potential of the data being produced at each level of the manufacturing process.
If you’re in the manufacturing industry, you may be wondering how you can unlock the power of big data within your organization.
The term “big data” is often spoken about, but its meaning is rarely made clear. To truly unlock the massive value of big data, it’s important to first understand what it is and what it isn’t.
Big data is a comprehensive term for all the processes and techniques that enable storing, organizing, and analyzing massive data sets. This can include billions of rows and parameter values. Sources for big data can include machines, devices, operators on the factory floor, and every level of your organization. For manufacturing, big data is made up of business-critical information on sensors, pumps, motors, compressors, and conveyors.
As you can see, it’s neither a single piece of software nor is it purely hardware-related. Simply moving your existing data infrastructure to the cloud also won’t immediately unlock the value of big data. Getting the fullest return on investment for the massive data sets being produced requires a data ecosystem, where the software your organization uses supports the infrastructure you already have in place.
One of the biggest benefits that big data can unlock is the ability to incorporate machine learning into your organization. Big data is necessary to feed algorithms that can predict, triage, and proactively solve problems within your organization.
Traditionally, manufacturing and other organizations use linear regression and absolute numbers to identify issues and opportunities. This can be in the form of human-monitored data visualizations, where a large drop in a machine’s output points to an issue in production. With machine learning, this process becomes automated and streamlined.
Machine learning on top of big data allows the identification of large-scale covariance and correlation, making root causality proactive and automatic. The benefits of big data mixed with machine learning extend to many other areas of the manufacturing process and are especially useful for these data sets, which are often noisy and especially large. This combination can be used to proactively identify machine failure, predict machine degradation, and optimize machine efficiency.
Big data helps manufacturers by:
Big data and its benefits rely on key principles to be in place. Without these, your organization won’t be able to reap any of the benefits of big data. These include:
Modern has built DataOS to include all of these elements, out of the box. It is an entire data ecosystem layered on top of your legacy or modern data infrastructure.
Learn more about Modern’s DataOS here. Or schedule a demo today to learn how DataOS can help you unlock the power of big data for your organization in a matter of weeks.
Be the first to know about the latest insights from Modern.
Customer data platforms (CDPs) are increasingly popular sources of customer insights. These systems are usually owned and operated by an enterprise marketing department and provide data for insights into customer trends, behavior, and customer 360 analyses....
Banking and Capital Markets are undergoing a period of transformation. The global economic outlook is somewhat fragile, but banks are in an excellent position to survive and thrive as long as they have the right tools in place. According to Deloitte’s report 2023...
Data center downtime can be costly. Gartner estimates that downtime can cost $5,600 per minute, extrapolating to well over $300K per hour. When your organization’s digital service is interrupted, it can impact employee productivity, company reputation, and customer...
Once upon a time, Gartner predicted that 40% of all data science tasks would be automated. Naturally, this caused some discussion about the future of the profession and whether it would still be the hottest position on the market. However, as the field progresses,...
One of the biggest reasons societies band together to create a governing body is to help care for members of that society. Government should help us maintain a certain standard of living, help solve societal challenges, and mobilize when disruptions happen....
Looking to the Future - How a Data Operating System Breathes Life Into Healthcare
Get to the Future Faster - Modernize Your Manufacturing Data Architecture Without Ripping and ReplacingImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure...
Get to the Future Faster - Modernize Your Manufacturing Data Architecture Without Ripping and ReplacingImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure...
Enable a Data-Informed Government - Modernize Your Data Architecture Without Ripping and ReplacingImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV....
Unified Data Platform Weaves Distributed, Diverse, and Dynamic Data in Modern EnvironmentsImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV. In the...