At Eurostep, our approach to data management underscores a critical distinction between big data and small data, each with its unique characteristics and applications. During our “Leveraging AI* for built asset Digital Twins – Turning scattered data into strategic assets” webinar, we delved into this differentiation, illustrating how our strategies effectively leverage both data types for optimal results in the context of built asset digital twins.
Big Data: This is characterized by its large volume, but it often lacks diversity. Traditionally, big data is utilized in scenarios where the sheer volume of information is the primary focus, such as in data lakes. These data sets are valuable for analyzing trends and patterns over vast datasets.
Small Data: Contrary to big data, small data encompasses datasets with lower volume but higher diversity and entropy. The real power of small data lies in its rich details and semantics, which are crucial for in-depth, nuanced analyses. At Eurostep, we channel our efforts towards managing and integrating this small data into Knowledge Graphs. This approach allows us to delve deeper into the intricacies of the data, uncovering insights that might be overlooked in larger, less diverse datasets.
This strategic focus on small data does not undermine the value of big data; instead, it complements it. By combining the broad overview provided by big data with the detailed insights offered by small data, we create a comprehensive data strategy. This enables us to provide more accurate, actionable intelligence for our clients, especially in the complex field of built asset management.
Our approach is designed to ensure that, whether it’s the expansive scope of big data or the detailed richness of small data, the information is not just collected and stored but transformed into a strategic asset that drives informed decision-making and operational efficiency. This balanced approach to data management positions Eurostep as a forward-thinking leader in the field of data intelligence and digital transformation.