A key U.S. state law enforcement agency (LEA) wanted to increase both investigative capacity and capability, by being able to quickly identify and analyze the connections between disparate data sets.
With their previous approach, there was significant overhead associated with locating and pulling data from different systems and spreadsheets, and then trying to organize, connect, and analyze that data. A better approach held the promise of being able to increase efficiency, uncover new insights, and ultimately help reduce violent crime.
The LEA concluded that what was needed was a data platform and intelligence analysis system that could be used to connect and analyze a variety of disparate data sets. Key requirements included:
Team members of the LEA had prior experience with Palantir and IBM products, and considered these and other solutions. Palantir offered an attractive product but was price-prohibitive, while the IBM solution lacked the desired flexibility. The LEA selected DataWalk as it provided the compelling combination of extreme flexibility, ability to easily identify/analyze connections across disparate data sets, enterprise functionality, and an affordable price.
With DataWalk, the LEA is importing data from various sources, including:
Data is normalized in DataWalk using DataWalk Apps such as the Address Parser and PDF Parser. CDR data is automatically normalized to a consistent format, regardless of the telecom service provider. Data is connected in DataWalk in the Universe Viewer, a highly flexible knowledge graph where data is re-organized around relevant business objects such as people, phones, locations and so forth. This data can then be easily searched and visually queried via an intuitive visual interface.
Data can also be analyzed via link charts, which include DataWalk’s powerful graph algorithms enabling automatic detection of organized crime groups and distant connections. Data associated with a particular individual or event can easily be viewed in a DataWalk Folder, which is a single location where all data in the system associated with that object and its connections – generated from all data sources in the system - is available for review.
Though the LEA is continuing to collect the data sets to be used in the initial solution, they have been using DataWalk in preliminary work and are seeing the benefits of having all data connected in one place for visual analysis. For example, investigative activities have been accelerated by using DataWalk to trace hidden/distant connections associated with specific firearms. The LEA has been impressed with the DataWalk team, and initial results are promising. The LEA is looking forward to having all data sources available to them so that data can be loaded into DataWalk and production work can commence.