Systems | Development | Analytics | API | Testing

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management. Now, that’s changing. Snowflake's new dynamic tables feature redefines how BI and analytics teams approach data transformation pipelines.

Data is often described with cliches like, it's "the new oil" or “the new air.” No matter how you describe it, there is no denying the increasing importance of data monetization across every industry. Forward-thinking organizations recognize data apps as both a revenue stream and a differentiated service to increase customer loyalty.

It’s an exciting time to be in the world of data and business intelligence. Recent advances in AI and machine learning are not only changing the way we interact with data, but also pushing those of us who build analytics and BI platforms to think critically about how our products can best serve our customers moving forward. Some will always love getting hands-on with data—but that’s no longer the only option.

Every winter, members of ThoughtSpot’s research and development teams participate in a company-wide hackathon called Codex. The ideas that come out of Codex are always inspiring, but the Winter 22/23 hackathon was special—OpenAI had just released ChatGPT and the world was buzzing about generative AI.