Convergent Data is Here to Stay
Blog: Jim Sinur
The days of relying on one simple data source in any digital solution are numbered. There is a growing wave that combines multiple sources and types of data to maximize business results. Those organizations that ride this wave will thrive and capitalize on the changing conditions and emerging business moments. The best digitally-enabled organizations will leverage convergent data in new ways to stay relevant in their current business models, extend existing business models or invent new business models. This post will concentrate on the many tributaries to this evolving convergence.
Figure 1 Convergent Data Sources
Reasons for Convergent Data
Convergent data is a result of both push and pull trends. There is the push of technological progress that invades organizations with capabilities and results that are hard to pass up. As success breeds more success these new sources of data such as video, voice, and integrated video over GPS data, organizations are hard-pressed not to leverage some if not all of these new data sources. The pull comes from the increasing demand for deeper understanding represented by multiple traditional sources combines with new and progressing data sources. In other words, the problems demand more complicated and complex data sources.
Leveraging Convergent Data
All aspects of running an organization will need or even require convergent data. Convergent and more complete data sourcing helps organizations sense events or patterns of interest, define opportunities or threats, ideate potential responses, and experiment with or implement proper responses. Each step in design thinking requires richer data offered by convergent data sources.
Sources of Convergent Data
Refer to Figure 1 for an illustration of the typical sources of convergent data. Starting with the bottom of the chart with base data, moving up to the time continuum, and finally to the top, base data is organized into more functional groups of related data to save time and effort.
Operational Data is typically at the lowest level and considered as base data. Its domain definition is usually defined, such as text, numbers, etc., and relationship to other data.
Video/Image Data is typically a picture represented by pixels captured at a point in time representing positions, colors, objects, texture, and relative positions of multiple items to each other. Video is a set of successive images captured over time to create movement in time and space.
Voice Data is sound captured over a time continuum to represent inflection, volume, anomalies, and emotion to leverage in the capture, storage, and analysis for sentiment and reoccurring themes/events.
Instantaneous Data is the date that is captured at the moment of focus. It is often associated with a real-time signal, event and is often more usable as a pattern, especially from multiple sources. This kind of data is often related to the Internet of Things (IoT) but not exclusively.
Archival/Backup Data is older than in nature and deemed necessary to capture in a specific time corridor. It would be ready and prepared for backup data to replace current data in a short period to repair data loss. Most archival data kept for historical purposes and trend analysis.
Aggregated Data is base data grouped and organized in a fashion deemed useful for further processing or analysis. Often this data is from multiple sources and is often summarized for ease of use and access.
Management Data is data that helps organizations manage better at several levels. The most frequent service would be for describing operations to monitor or optimize operational activity. While less common, but more important would be to adjust management policies for better organizational outcomes. For ultimate impact, data would be leveraged to adjust major strategies to adapt to emergent threats or opportunities.
Time Series Data is data captured in predetermined time slots and quite often organized specific sequences. Typically this is detailed data, but it could be summarized or aggregated in other categories.
Organizations will either ride the convergent data wave, which typically creates views across multiple data sources, or get swamped by it. Convergent data is an unstoppable trend that promises new revenue sources, better situational awareness for operational optimization, and better customer engagement sources. The challenge here is managing all this convergent data smoothly. There are emerging methods, techniques, and technologies ready to assist this portion of digital transformation.