Analytics

In keeping with its continued focus on building the most powerful and flexible cloud data platform for data-driven companies, Snowflake released a host of new features in July. The following roundup briefly describes several of them.

Linear regression, alongside logistic regression, is one of the most widely used machine learning algorithms in real production settings. Here, we present a comprehensive analysis of linear regression, which can be used as a guide for both beginners and advanced data scientists alike.

One of the key challenges of building an enterprise-class robust scalable storage system is to validate the system under duress and failing system components. This includes, but is not limited to: failed networks, failed or failing disks, arbitrary delays in the network or IO path, network partitions, and unresponsive systems.

Pixel-perfect reports are a highly specific formatting capability that requires the right business intelligence (BI) solution to meet your needs for precision, quality and design. However, you may be surprised to learn it’s often not an out-of-the-box feature in 2020.

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.

More than ever, businesses are making real-time, data-driven decisions based on information stored in their data warehouses. Today’s data warehouse requires continuous uptime as analytics demands grow and organizations require rapid access to mission-critical insights. Business disruptions from unplanned downtime can severely impact company sales, reputation, and customer relations.

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.