Systems | Development | Analytics | API | Testing

What's New in ThoughtSpot's Latest Release

Check out what’s new in ThoughtSpot’s latest release! Access data literacy skills within Spotter, and have your agent explain the data model. Now also offering contextual suggestions for questions and additional details on calculations. KPI alerts can now also trigger only for specific attributes and values, enabling more focused and contextual decision-making. Fully customize your user interface by using String IDs for custom system text in white-labeled scenarios.

How a CDAO goes from baseball to insurance with Don Vu - New York Life

Step inside the world of data innovation as Cindi Howson talks with Don Vu, SVP and Chief Data and Analytics Officer at New York Life. They'll reveal how a 180-year-old institution is leveraging cutting-edge AI to make experiences proactive and intelligent. Hear how New York Life utilizes their innovative "GuideMe" tool to supercharge agent and client financial planning, tackles the "last mile problem" in data operationalization, and ensures data quality is paramount for both structured and unstructured data.

ThoughtSpot is a Leader in the next era of Agentic Analytics and BI

For too long, businesses have been adrift in a sea of static dashboards and colorful visualizations, mistaking activity for insight. They call it business intelligence, but in reality, it's just more noise. These legacy dashboards are inherently unintelligent; they might answer your first question, but they immediately force you to create ten more dashboards to get subsequent answers. It’s a vicious cycle of dashboard sprawl, not true intelligence.

Introducing the ThoughtSpot Visualization Platform

Whether you're exploring trends, uncovering outliers, or designing presentations that tell a compelling story, your insights should be connected and pervasive. It's no longer enough to simply see your data. You need a fluid, intuitive experience that empowers you to find next-level insights faster. We’re thrilled to announce ThoughtSpot’s new-and-improved visualization platform, built with integrated intelligence to empower limitless interactivity.

Meet Muze: ThoughtSpot's native visualization engine

Business intelligence platforms analyze vast amounts of data, requiring visualization engines that balance performance, flexibility, and ease of use. Traditional charting libraries treat each chart type as a distinct entity, requiring separate logic and code for each. This approach leads to code duplication, limited reusability, and reduced maintainability. Additionally, it’s cumbersome to effectively layer or combine visual elements due to these libraries’ rigid composability.

Introducing the Agentic Semantic Layer: A New Standard for Data Foundations

For data analysts and engineers, the journey from raw data to actionable business insights for business users is never as simple as it sounds. The semantic layer is a critical component in this process, serving as the bridge between complex data sources and the business logic required for informed decision-making. However, not all semantic layers are created equal, and the evolving landscape of AI-powered analytics demands a new approach.

Unleashing AI-Driven Innovation: ThoughtSpot's Momentum in Australia & New Zealand

At ThoughtSpot, we’re on a mission to empower every business user to become a data champion. Over the past year, I’ve witnessed firsthand how organizations across Australia and New Zealand are embracing this vision, transforming the way they work, make decisions, and serve their customers. Today, I’m excited to share some of the incredible momentum we’re seeing in the region and to celebrate the forward-thinking organizations leading the charge.

Data and AI Predictions for 2025 with Joe Reis

Navigating the evolving landscape of data engineering in the age of AI? Join us as we delve into a crucial conversation with @JoeReisData renowned author of "Fundamentals of Data Engineering" and the highly anticipated "Mixed Model Arts." Joe shares his expert insights on why robust data modeling remains paramount, the urgent need for data teams to upskill in this new era, and the transformative potential of a universal semantic layer.