How IX Leaders Look At Data: Casting a Wide Net and Building DataOps Function
Author: Patrick Fetterman, Research Analyst, LNS Research
Abstract
One of the major driving factors for Industrial Transformation (IX) is recognition of new ways to use the data generated in factories and plants, empowering new business insights that were previously unreachable. In fact, gathering and utilizing operational data has become the foundation for virtually all IX initiatives and technologies.
Yet, as it turns out, many companies are still lacking an enterprise data model that includes operational data, or a converged IT-OT organization that has the expertise to manage both IT systems data and data from operations technology, especially the enormous quantities of time-series data from PLCs and other factory systems. More importantly, many more organizations have given little thought to the next architectural component focused on data, data conditioning and contextualization.
Complete the form below to download the full report and learn:
Author: Patrick Fetterman, Research Analyst, LNS Research
Abstract
One of the major driving factors for Industrial Transformation (IX) is recognition of new ways to use the data generated in factories and plants, empowering new business insights that were previously unreachable. In fact, gathering and utilizing operational data has become the foundation for virtually all IX initiatives and technologies.
Yet, as it turns out, many companies are still lacking an enterprise data model that includes operational data, or a converged IT-OT organization that has the expertise to manage both IT systems data and data from operations technology, especially the enormous quantities of time-series data from PLCs and other factory systems. More importantly, many more organizations have given little thought to the next architectural component focused on data, data conditioning and contextualization.
Complete the form below to download the full report and learn:
- What three behaviors set IX Leaders apart compared to their peers
- Why data science teams have struggled to make an impact
- How the emerging idea of DataOps will change the way manufacturers manage data, hire new talent, and organize their teams
- What four best practices can help companies get a good start in their IX initiatives
Photo credit: Elle Darcy
