As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts. Private cloud continues to gain traction with firms realizing the benefits of greater flexibility and dynamic scalability.
Today we’re excited to announce the general availability of the Snowpark API for Scala and Java UDFs on AWS. Snowpark is the developer framework for Snowflake, bringing deep, language-integrated data programmability to users in the languages they love. At its core, Snowpark is all about extensibility.
During the holiday break, our family had to get tested for COVID. We got at-home tests, as they were available, and it was easier than having to wait in line at a testing center. This got me thinking of a recent article in the New York Times, which raises the notion that experts are questioning the importance/value of measuring COVID caseloads with the rise in the use of at home tests.
According to 451 Research, 96% of enterprises are actively pursuing a hybrid IT strategy. Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. Cloud technologies and respective service providers have evolved solutions to address these challenges.
The start of a new year is a perfect time to reflect on what was accomplished and look forward, re-evaluate what we can do better. Change, although difficult at first, can also be very rewarding. That’s why I was excited to see similar sentiments shared at Thoughtspot beyond.2021 to move beyond the traditional dashboards of the past.
Organizations increasingly turn to AI to transform work processes, but this rapid adoption of models has amplified the need for explainable AI. Explaining AI helps us understand how and why models make predictions. For example, a financial institution might wish to use an AI model to automatically flag credit card transactions for fraudulent activity. While an accurate fraud model would be a first step, accuracy alone isn’t sufficient.
