Unlocking The Full Potential of Enterprise Data
Moreover , becoming a digital enterprise is a major steppingstone towards achieving true marketfacing digital transformation , which provides the greatest value and competitive advantage . Digital enterprises are at the heart of the concepts of digital engineering and digital threads .
1.3 BIG DATA
As an enterprise becomes a digital enterprise , the volume of data produced by a proliferating number of digital systems ( digital twins , AI , IoT and more ) and consumed by the digitalized processes will skyrocket � . Examples include IoT sensors that generate massive amounts of operational data , supply chain partners that exchange significant volumes of data related to inventory and product and component information . This data can be fed into digital twins and analytics engines to generate insights , make decisions , and create even more data which in turn may be exchanged again with ecosystem partners .
The resulting volume of data exhibits many typical “ V ” characteristics associated with big data :
• Volume : The volume of this data ( operations , engineering , etc .) is massive 6 and potentially dwarfs the volume of corporate information produced by business systems .
• Variety : Data used by digital twins and IoT systems is quite different from data used in traditional business systems in both 7 format and modalities . There are also differences in architecture and data sources ( edge ) and storage locations within the infrastructure . As a result , traditional IT best practices developed for business systems need to be adapted or even redefined .
• Velocity : Given the highly distributed nature and demanding performance 8 requirements of IoT systems ( sensors / edge / cloud ), data moves through the enterprise architecture and beyond at high velocity and in all directions . This requires the organization to address the unique performance , latency , scalability and security characteristics of industry data , in all their states : at-rest , in-motion and in-use .
• Value : For many organizations in industry sectors , industry data represent valuable Enterprise Information Assets which must be governed . More about this in Chapter 2 .
Other V-characteristics of big data apply here , for example veracity and variability .
1.4 RELATIONSHIP BETWEEN INDUSTRY DIGITAL TRANSFORMATION AND DATA
The interplay between digital transformation and data volume is symbiotic . DX initiatives generate vast amounts of rich and granular data that informs decision-making , optimizes processes , and personalizes user experiences . In turn , this data accelerates transformation by providing deeper insights , enabling process automation , and fostering innovation and agility . It
6
More than 70 zettabytes of IoT data in 2025 according to Statista .
7
Time series , spatial data , indexed video and images , IR video and images , etc .
8
Example : low latency . 36
February 2025