Data preprocessing is often the most challenging step in any data-driven project, especially when dealing with inhomogeneous data.  

LEA crime investigation data comes in various formats, structures, and quality levels, requiring complex data cleaning and transformation processes. The above process can be further complicated by inconsistent missing values, and diverse encoding standards. Without a curation methodology and a common model, the process is prone to errors, hard to scale and therefore the LEA’s case investigation becomes time-consuming.  

A standardized approach, like the TRACY ingestion process, can simplify processing, enhance data quality, and make downstream analysis, either descriptive or predictive, more efficient. Investing in unified preprocessing methods is no longer just a technical necessity—it’s a strategic advantage for any data-centric organization. 

Having standard models for representing crime cases has another advantage: Observability.  The ability to visualize, observe, and analyze crime data provides a better understanding of the events associated with a crime, the suspects, and the level of their guilt. The TRACY platform includes several tools to support the observability methodology. 

Figure – A visual representation of communication between suspects