Thousands of Real-Time Models in Production
Hear from Kaegan Casey, AI/ML Solutions Architect at Seagate, discuss how his team uses MLRun to train thousands of models in parallel.
Solving ETL Challenges with Apache Kafka, Confluent Tableflow, and Zero ETL
Operational and analytical estates have been separated since data warehouses were first introduced in the 1990s. The operational estate includes microservices, software-as-a-service (SaaS) apps, and enterprise resource planning systems (ERPs) that have become the beating heart of an organization. The analytical estate consists of the data warehouses, lakehouses, artificial intelligence (AI)/machine learning (ML) platforms, and other custom batch workloads that support business analysis and reporting.
ThoughtSpot Agentic MCP Server Demo
Unlock the full power of your AI agents! This demo shows you how easy it is to use ThoughtSpot's Agentic Model Context Protocol (MCP) Server to bring comprehensive, trusted analytics directly into your favorite AI platforms like Anthropic Claude, Google Gemini, and OpenAI ChatGPT. No more switching between tools! See how you can combine structured data analysis from your ThoughtSpot Models with insights from unstructured data, all through a single natural language prompt in Claude. You'll go from a question to an AI-augmented dashboard (ThoughtSpot Liveboard) in just a few minutes.
Introducing ThoughtSpot's Agentic MCP Server
The AI agent revolution is transforming how we work, but most analytics platforms are stuck in the past—forcing you to context-switch between your agents and separate BI tools to get data insights. This fragmented approach creates friction, breaks workflows, and ultimately slows down decision-making. When speed matters most, you need your AI agents to seamlessly access and analyze enterprise data without the traditional barriers of maintaining custom integrations and limited API functionality.
Why Shift Left Matters in Modern Data Architecture
The shift left paradigm isn’t just a developer trend, it’s how Swedbank bakes in data governance, compliance, and security from the start.
Streamlining AI Workloads: How ClearML's Infrastructure Control Plane Automates Orchestration, Scheduling, and Resource Optimization
By Noam Harel, Co-founder and CMO, ClearML AI is certainly transforming industries, but delivering it at scale is a harder task The shift to enterprise-grade AI isn’t just about building better models. It’s about managing the growing sprawl of infrastructure, tools, and people involved in every phase of your AI production From building and training to production deployment, teams are bogged down by fragmented workflows, manual provisioning, inconsistent environments, and underutilized compute.
One piece of content = 10x the impact
Can your blog post turn into a video? Can your case study help the sales team and customer success? If so, you’ve got high-value, sustainable content that sells itself — even to your exec team. Amanda Natividad, VP of Marketing at @SparkToro breaks down content sustainability — the key to scaling marketing without burning out. Databox is Modern BI for teams that need answers now. It offers the best of BI, without the complicated setup, steep price, or long learning curve.
How Conversational BI Solves Key Analytics Challenges
Creating dashboards and reports shouldn’t require a technical background, or hours of your users’ time. When applications lack user-friendly analytics, customers are forced to depend on IT just to understand their own data. That’s where conversational BI comes in. Whether you’re a business leader or a data analyst, conversational BI adapts to how you work, learns your preferences, and helps you move from question to insight faster than ever before.
How AI is Revolutionizing Finance Teams (With Real Examples)
The journey from disconnected data silos to self-service automation and predictive visibility is well underway for many finance organizations. But the million-dollar question remains: what’s the actual return on investment from this transformation? Beyond time savings and process improvements, modern finance transformation drives strategic value that directly impacts the bottom line. Adding AI into the mix turbocharges these benefits.