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Data Fusion


There is a fire hose that is throwing out a large amount of data into our world today. It is commonly known as Big Data. However, due to the disparate sources of data, this data is not homogenous. In the absence of homogeneity, it is impossible to build data models that accurately amplify any signal. Data Fusion is the ability to take disparate data sources and create a homogenous whole that is useful. This is done in geographic units say One Square Kilometer. At Quantta, we have built proprietary tools and API’s that allow data ingestion using automated tools. Our algorithms then go to work to standardize, organize and make this data useful to our data scientists.

  • Multiple Data Sources
  • Sourcing data from disparate sources and blending this data
  • Geographic Homogenization
  • Homogenization of data into a common geographic format to make it useful
  • Structuring Data
  • Converting data from unstructured format to structured usable formats
  • Isolating Useful Data
  • Identification of data that is able to predict consumer insight
  • Quantifying Data
  • Using algorithms to quantify what the data is telling us