It almost seems like eons ago now, but in this year’s Gartner Data and Analytics Sydney Summit, Yellowfin were excited to participate in the first-ever Analytics & BI Showfloor Showdown, alongside IBM and Oracle. As a way of facilitating a side-by-side comparison - and in the spirit of an insightful and entertaining session - we were all invited to look at the WHO health indicators data set, understand the variables that drive life expectancy, and present them to the crowd.

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.

In today’s digital age there are numerous websites that compete to drive traffic to their portals. They invest heavily in strategies like SEO and SMM to get visitors hooked on their content. Getting traffic on your website is important but it’s also critical to understand how visitors interact with your content. This is where website analytics tools and solutions come in.

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.

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.