The executive administrator from the Commercial Tax division recruited a data science team to ferret out leads for the auditors. The team took the time to digest and understand the clues that the state audit team had shared with them about this hot tip.
To be able to make better sense of the state’s data, the team decided to enrich it by matching against external data from infoUSA. DataMatch Enterprise was used to link those records/clues/attributes/fields of information from infoUSA to the decades of data that had been collected but never mined, within the state’s Teradata system.
Using DME to match up the external and internal data, the team was able to make the data more usable and contextual for analysis. They then layered their data science on top of this stable foundation, building models and running routines until they narrowed down the potential leads that the commercial auditors could chase – from nearly 2 million records to 100k records.