Could data analytics make for a safer, more transparent food supply? Maria Fernandez Guajardo, VP of Products at Clear Labs, answered that question with an unequivocal “Yes!” when she presented at the recent Intel Analytics Summit.
Collaboration Drives Better Data
Clear Labs exists at the intersection of genetic analysis and data science, analyzing food at the molecular level to generate information for the food industry about the authenticity and safety of their ingredients and finished products. In her Analytics Summit talk, Maria demonstrates how the company employs a combination of database and analytics technologies to analyze the food supply, including an unbiased and universal DNA test, machine learning probabilistic species identification, and a proprietary reference database with millions of sequences.
Science aside, Clear Labs is a great example of some groundbreaking trends in data analytics. One of those trends is the push to make the results of data analytics investigations more useful by driving closer collaboration among data scientists, developers, business analysts and marketing people. The goal is to generate information that is meaningful not just to data scientists and analysts, but to the broader public. This is the type of collaboration that gave rise to the Clear Labs “Hot Dog Report,” a study of the U.S. hot dog quality landscape.
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