Historically, it was nearly impossible for a large enterprise to optimize the use of geospatial data and specifically in relation to other datasets and attributes. Tamr is leading the charge by evolving our data unification platform to natively understand geospatial data to help enterprises achieve analytical breakthroughs and transformational outcomes.
So, how does it work? For use cases where site data is an important element, Tamr’s agile data mastering solution can incorporate geospatial data (points, lines, polygons, etc.) into its machine learning-driven matching. Tamr understands the distance between points or objects and integrates that as a factor within our mastering models to run deduplication algorithms, transform data, or create golden records. In the image below, Tamr is suggesting with high confidence that the highlighted pair of records is a potential match based on several attributes, and Tamr is illustrating the geospatial similarity between these records to provide context to the subject matter expert who will verify this suggestion.
The ability to integrate geospatial site data within the overall agile data mastering process significantly accelerates time to value, providing visual context for more accurate and trustworthy results than could be achieved with addresses or other textual data alone.
In the petrochemical industry there is an immense need for mastering projects not only to ingest, but also to understand geospatial data. Oil formations, regulatory zoning, extraction and refining sites, and pipelines cover areas, not just a single point. In legacy data management systems, oil & gas formations and wells are treated as discrete points; so even with clean data, analytics of data mining projects are using approximations of the actual expanse of these sites. This approximation requires significant manual effort to reconcile data points with the actual physical formations, let alone to prepare such data for analysis and meaningful presentation.
The benefits of using Tamr to help solve these problems include:
Tamr’s ability to ingest and process polygon data can drastically improve harmonization of wells and facilities to reap efficiencies through geospatial data analytics
Tamr can efficiently cluster buildings, suppliers, retailers, etc. for site planning purposes, revealing an accurate picture of holdings for effective coverage of commercial areas
Tamr can reconcile diverse sources of information about land, maritime, or low altitude aerial routes to permit optimal wayfinding and hazard avoidance for cargo ships, trucks, or drones