Systems | Development | Analytics | API | Testing

Tired of Surface-Level Analytics? Yellowfin's AI Powered Insights Gives You the Full Picture

Have ever opened up a dashboard or report, and not known where to start exploring? Finding meaningful conclusions from a sea of charts and tables can be challenging and time-consuming. It's not always easy to see and understand the story your data is trying to tell, especially when you’re presented with a lot of information at once.

Your Data Has a Story to Tell: Yellowfin 9.16 Helps You Find It

The future of analytics is conversational, and with Yellowfin 9.16, it's here today. This release introduces a suite of AI-powered features designed to fundamentally change how you interact with your data. Forget complex queries and manual report building; now, you can simply click a button and get instant insights, charts, and narratives. Let's explore how.

What is the Parquet File Format? Use Cases & Benefits

Apache Parquet has become the de-facto standard for storing data used in analytics workloads, and has seen very broad adoption as a free and open-source storage format. When used as the underlying storage layer for Apache Iceberg, Parquet is also a foundational building block in modern lakehouse architectures, which enable warehouse-like capabilities on cost effective object storage. Let’s take a closer look at what Parquet actually is, and why it matters for big data storage and analytics.

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.

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.

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.

AI is Reshaping Data Centers - Is it Time to Rethink Storage?

As artificial intelligence (AI) reshapes industries, it’s quietly revolutionizing the heart of IT: The data center. The explosive growth of AI workloads is driving up power usage, challenging cooling systems, and demanding a fundamental rethink of how we store and move data. In this new landscape, flash storage stands out – delivering the performance, efficiency, and scalability that AI needs to truly accelerate.