Genomic data is some of the most complex and vital data that our customers and strategic partners like Mayo Clinic work with. Many of them want to work with genomic variant data, which is the set of differences between a given sample and a reference genome, in order to diagnose patients and discover new treatments. Each sample’s variants are usually stored as a Variant Call Format file, or VCF, but files aren’t a great way to do analytics and machine learning on these data.

The current economic climate has meant a sudden and seismic step-change in how many of our customers operate. The recent shift to remote working has seen an increase in conversations around how data is managed, with many businesses needing to achieve democratic data access in order to derive value and improve efficiencies as we navigate the ‘new norm’. Toolsets and strategies have had to shift to ensure controlled access to data.

We’ve been busy speaking to our customers and thought leaders in the industry and have rounded up the key takeaways from our latest CDO sessions. Here are some of the top takeaways and advice gained from these sessions with big data leaders, Kumar Menon from Equifax, Anheuser-Busch’s Harinder Singh, Sandeep Uttamchandani from Unravel, and DBS Bank’s Matteo Pelati.

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We recently Googled the manufacturing use case “predictive maintenance” and was astonished by the results there were 82 MILLION results returned. Next, we Googled “process optimization” and it yielded even more results – 302 MILLION. Clearly, these use cases are top of mind in today’s manufacturing landscape, considering digital transformation will deliver $11 Trillion USD in economic value by 2025.

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