Webinar: The Problem with Traditional Analytics - Part 1

Qrvey is the analytics platform that solves today’s biggest analytics challenges, and to prove it, we’re launching a new three-part webinar series simply entitled “The Problems with Traditional Analytics.”

In part one, we’ll be exploring the dark data problem, which is simply that traditional analytics leaves up to 70% of your business data behind. Legacy products can’t process semi- and unstructured data and they aren’t equipped to handle the volume, velocity and diversity of today’s business data. That means your business isn’t seeing the complete data picture or worse, is making decisions based on incomplete, inaccurate or outdated data.

In our webinar, we’ll detail all of the dark data pitfalls and show you how to fix them with a modern, cloud-native analytics platform. Space is limited, click the link below for a list of available dates/times.

In parts two and three of the webinar series, we’ll take a deep dive into the two other biggest challenges of traditional analytics, performance and user adoption.

See a list of all of our upcoming webinars.

David Abramson

David is the Chief Technology Officer at Qrvey, the leading provider of embedded analytics software for B2B SaaS companies. With extensive experience in software development and a passion for innovation, David plays a pivotal role in helping companies successfully transition from traditional reporting features to highly customizable analytics experiences that delight SaaS end-users.

Drawing from his deep technical expertise and industry insights, David leads Qrvey’s engineering team in developing cutting-edge analytics solutions that empower product teams to seamlessly integrate robust data visualizations and interactive dashboards into their applications. His commitment to staying ahead of the curve ensures that Qrvey’s platform continuously evolves to meet the ever-changing needs of the SaaS industry.

David shares his wealth of knowledge and best practices on topics related to embedded analytics, data visualization, and the technical considerations involved in building data-driven SaaS products.