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By Antonio Scaramuzzino
Most teams deploying AI agents on their data are watching the wrong things. They check whether the query ran and whether the number looks plausible. When both checks pass, the agent gets credit for a correct answer, and the output flows into dashboards, decisions, and the next agent in the chain. There's a gap between those two checks and actual correctness, and it's where the expensive mistakes live. Getting to a correct answer requires more than a formally valid calculation.
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By Ashok Anand
4,096 Tasks completed 89.8% success rate 302 Active users 4× growth Jan→Mar 86 Agents deployed 73 built by engineers 72 days In production 15,896 messages Modern engineering teams face a familiar paradox: the bigger the system, the more time engineers spend managing the work rather than doing it. Bugs pile up faster than they can be triaged. PRs wait days for review. On-call engineers spend hours reproducing what someone already debugged six months ago.
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By Damian Waldron
In 1799, soldiers near Rosetta, Egypt, unearthed a stone carved with the same decree in three scripts: hieroglyphs, Demotic, and Ancient Greek. Because scholars already understood Greek, it unlocked a language—and with that, a civilization’s worth of knowledge that had been dark for over a millennium. We’re at a similar inflection point in enterprise data.
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By Lindsay Lukens
AI-powered analytics is everywhere right now. But the payoff? Not so much. Two patterns show up again and again. The first is an “AI everything” backlog that expands faster than teams can deliver. The second is an insights bottleneck that still forces the business to wait in line for basic answers while analysts drown in ad hoc requests.
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By Jessica Hwang
Your data’s never lived in one place. Customer records might be in your CRM, while sales and operational metrics are split among data platforms. And somewhere, there's critical budget data living in a spreadsheet, owned by a single person on the finance team. Bringing it together has always come at a cost of speed vs. governance.
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By Peeyush Vardhan
Every analyst has been there: Deadline looming, data in hand, and a BI tool that either requires a workflow you haven't learned or a colleague you can't reach. So you open Excel. It's familiar, it's flexible, and it works right now. So that's where the work happens—and now where insight stays, ungoverned and invisible to your team, your analytics stack, and your agents.
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By Nishant Taneja
We launched Spotter with one goal: give every enterprise team their own analyst—an agent that reasons through business complexity, validates its own outputs, and surfaces answers you can actually act on. The response from customers made one thing clear: the ThoughtSpot foundation works. Teams trust Spotter, because it doesn’t only rely on an LLM to reconstruct your business logic on the fly—a process that produces different answers depending on how a question is phrased.
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By Damian Waldron
AI can now generate SQL, build dashboards, and answer questions in plain language. But generating queries isn’t the same as understanding a business. The model might not know which revenue definition finance approves, how your fiscal calendar works, or which fields require restricted access. As AI agents become the front door to analytics, the real challenge isn’t query generation; it’s semantic grounding. That’s where the Agentic Semantic Layer becomes essential.
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By James Smith
The EMEA region is undergoing a massive transformation, driven by companies demanding instant, actionable insights embedded directly into their applications and workflows. This fundamental shift away from legacy BI has translated into record-breaking momentum for ThoughtSpot, positioning EMEA as our fastest-growing region globally. The Agentic Analytics revolution is here, and ThoughtSpot is delivering on the promise to make the world more fact-driven.
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By Anjali Kumari
One year ago, we introduced Analyst Studio, ThoughtSpot’s unified workspace for preparing and managing AI-ready data, with a vision: to transform analysts from report generators into business catalysts. SQL, Python, and visual analysis finally worked together in one workspace, letting data teams move seamlessly between ad-hoc queries and advanced modeling, all while preparing data for the AI revolution we knew was coming.
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By ThoughtSpot
Don’t let the "AI iceberg" sink your IP Most leaders only focus on the flashy models at the surface, but the real value—and the risk—is what’s underneath. Tony Seale and Jessica Talisman reveal why turning AI back onto your own data infrastructure to build connected ontologies is the key to security. This semantic foundation is the core of Agentic Analytics, ensuring your insights are grounded in your specific business logic rather than generic LLM guesses.
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By ThoughtSpot
Is your AI-driven "autonomous enterprise" a reality or a peak-of-inflated-expectations dream? Most organizations rush toward the end state of AI agents without doing the foundational work of defining how their data actually relates through a robust ontology. In this episode of The Data & AI Chief, we sit down with Tony Seale, Founder of The Knowledge Graph Guys, and Jessica Talisman, CEO and Founder of The Ontology Pipeline. We break down why the "lost art" of data modeling and the development of semantic layers are the secret weapons for scaling Agentic Analytics.
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By ThoughtSpot
Learn why an organization’s ontology, a structured framework for how a business defines, connects, and makes sense of its data and knowledge, is the most valuable and most overlooked asset in any AI strategy. Jessica Talisman, CEO and Founder of The Ontology Pipeline, and Tony Seale, Founder of The Knowledge Graph Guys, break down what it actually takes to build trusted AI, covering everything from semantic layers and knowledge graphs to why provenance is non-negotiable.
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By ThoughtSpot
Are you spending too much time hunting down data assets across your cluster? Manually tracking every table and model shouldn't be a full-time job—it's time to let your metadata do the heavy lifting. In this walkthrough, we show you how to generate a comprehensive list of every table and model in your system to give you the clarity needed for optimization and cleanup. By leveraging CS tools to execute metadata commands and navigating the ts-metadata-objects folder, you can identify critical logical tables and capture object subtypes with precision.
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By ThoughtSpot
Tired of manual reporting workflows holding back your team? Learn how to scale your data distribution by mastering Liveboard exports through both the UI and ThoughtSpot’s REST API v2. In this walkthrough, we dive into the technical details of capturing specific tabs and formatting reports in high-quality PDF and XLSX. We’ll show you how to use identifiers and filters to customize insights—like a brand manager automating reports specifically for Coca-Cola—so your stakeholders get exactly what they need, when they need it.
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By ThoughtSpot
Why do most BI tools feel like they were built for someone else? Because they were built to be general—and "general" doesn't cut it in the Agentic era. At our March Spotlight, ThoughtSpot CMO Micheline Nijmeh introduces the unveiling of Spotter for Industries: AI designed from the ground up to understand your specific metrics, workflows, and priorities. We’re moving past the hype to deliver real business results.
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By ThoughtSpot
This is one question a banking team can ask Spotter right now, "Which customers are likely to churn based on declining balance activity over the last 90 days?" No ticket to the data team, no waiting on a dashboard build, and no SQL. Just a plain-language question and an answer your retention team can act on today. That's the shift from reactive reporting to agentic analytics. Your data answers back.
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By ThoughtSpot
Your customer service team flags churn risk in a quarterly review. Your product team spots low adoption in a dashboard two weeks later. By the time anyone acts, the customer is already gone. The delay is the real cost of fragmented analytics in software companies. Spotter for Software and Tech surfaces those signals in real time. It connects product usage, sales pipeline, and customer health data so that teams can ask questions like “Which accounts dropped engagement this month and what changed?” This way, they get answers quickly and can act immediately.
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By ThoughtSpot
Is AI a tool or a threat? Wharton Professor Stefano Puntoni explains why "self-preservation mode" is killing AI adoption in the workplace. Puntoni joins Cindi Howson (The Data Chief host) & breaks down why AI isn't a strategy—it's a tool that requires a "meet in the middle" approach. To succeed, leaders must provide the vision and resources, while empowering workers to co-create the roadmap.
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By ThoughtSpot
Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact.
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By ThoughtSpot
For more than 20 years, dashboards served as a foundational element of business intelligence, helping leaders visualize and share valuable data across their organization.
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By ThoughtSpot
Businesses today run on apps, and those apps run on data. Too often, however, the technical complexity required to surface and explore that data for additional analysis prevents users from doing so. With ThoughtSpot Everywhere, organizations are easily building new data apps powered by the simplicity and ease of use of ThoughtSpot, or adding ThoughtSpot services to their existing SaaS offerings. This is giving them the unprecedented opportunity to create product experiences that stick, monetize data in new ways, and harness data right within existing tools.
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By ThoughtSpot
We are living in an unprecedented time driven by rapidly changing economic scenarios, the rise of digital native organizations and growing digital revolution, and the emergence of transformative business models. At the heart of much of this revolution is data. Organizations are collecting, analyzing, and mining data at an accelerated rate, creating new opportunities for powerful insights that deliver significant business impact.
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By ThoughtSpot
Today, just 24% of organizations say they've succeeded at becoming data-driven.* This is a challenge many data leaders are still struggling to solve despite increasing demand for data-driven insights from business users. Migrating to a cloud data warehouse is a good first step-and many have done so-but introducing new technology is not the same as ensuring adoption. To truly reap the benefits of your cloud data warehouse investment, you need an equally fast, scalable, and easy-to-adopt analytics solution to make your cloud data available to all.
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By ThoughtSpot
Despite huge investments in data and analytics over the last two decades, many companies are still struggling with how to become truly data-driven. What are data leaders doing at the organizations that have figured it out? In this white paper, DATAcated Academy's Kate Strachnyi explores four key strategies for critically evaluating your entire data and analytics stack and systematically removing the barriers that exist between their business users and business-critical insights.
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By ThoughtSpot
Although making predictions about the future is difficult even under the best of circumstances, it's never been more important for business leaders to focus, prioritize, and act in order to stay ahead of the technological curve-and the competition. The strategies you used to innovate and grow your business in the past will not be the same ones you use today. Rethinking how you use data to react and proactively adapt to change will be critical to your bottom line.
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ThoughtSpot is the Modern Analytics Cloud company. With ThoughtSpot, you can put the full power of your modern data stack in the hands of every employee and customer with consumer-grade analytics.
Why Everyone Loves ThoughtSpot?
- Instant Insights for all: Stop waiting for custom reports from data experts and instantly answer ad-hoc data questions on the fly.
- Unleash the value of your cloud data: Maximize the value of your cloud data warehouse and accelerate speed-to-insight for everyone across your business.
- Build Interactive Data Apps: Drive adoption by embedding search and insight-driven actions into your apps using our low-code developer-friendly platform.
- Bye-bye backlog: Empower non-technical people to answer their own data questions, while you build a single source of truth with security and governance at scale.
Welcome to the Modern Analytics Cloud.