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We're excited to introduce a major update to the Choreo CLI: support for the Model Context Protocol (MCP). This enhancement brings conversational AI capabilities into your development workflow, enabling you to manage your Choreo environment using natural language commands.

Environmental, social, and governance (ESG) reporting is no longer just a rising trend—it’s a fundamental part of how companies demonstrate accountability, resilience, and long-term value. Investors, stakeholders, and regulators have made it clear: ESG performance is now inseparable from financial performance.

Welcome to the latest entry in Yellowfin Japan’s long-running ‘How to?’ blog series. This series of blogs aims to provide a step-by-step guide of how to get the most out of your Yellowfin BI experience, such as how to create your own Yellowfin dashboard, and how to use Yellowfin's rich data visualization tools. Catch up on the series below.

Let's talk about a problem that might sound simple but gets complex quickly: copying data from one Kafka cluster to another. As our Kafka usage grows, many of us find ourselves managing multiple clusters and needing to share data between them. Or worst still, sharing data to an external cluster. During a London meetup, we explored why this happens, what existing solutions offer, and why we decided to build our own Kafka replicator. Here's what we learned.

Reverse ETL delivers personalized experiences, smarter campaigns, and better decisions with operationalized data.

Agriculture has long been the backbone of human survival, proof of our deep connection with and dependence on nature. But as the world evolves, so do the challenges in farming. From shrinking arable land to unpredictable weather patterns, how can farmers keep up? How do we ensure there's enough food for future generations? There’s no doubt that farming has come a long way, but let’s be honest, it’s getting harder every year.

When you think of artificial intelligence in transportation, what’s the first image that comes to mind? Is it self-driving cars smoothly cruising city streets, or maybe delivery drones zipping through the skies? While the dream of fully autonomous vehicles might still be on the horizon, the reality is that AI is already reshaping how we move, every single day. Look how our Co-founder is enjoying the view in a self-driving car in the USA! ‍ Yes, you saw that right, it’s fully autonomous.

How does GDPR impact AI innovation, and what affects might AI have on regulations like GDPR? According to McKinsey, 78% of companies now use AI in at least one area of their business as of July 2024. But this quick adoption brings challenges for organisations handling data from the European Union and the UK. The main challenge for InfoSec and other enterprise leaders is clear. Using AI effectively means being able to develop faster.

The demand for AI-driven applications is surging, and enterprises have reached an inflection point where they can no longer afford fragmented, siloed development. Traditionally, AI development is done by data scientists or machine learning experts with deep expertise in multiple tools and frameworks.

Every day, finance teams using Oracle ERPs find themselves bogged down by the inefficiencies of manual processes—relying on spreadsheets, juggling data extracts, and waiting on IT for access to the information they need. Even with Excel as the go-to tool, managing large datasets and producing accurate reports becomes a time-consuming ordeal, pulling focus away from strategic analysis and decision-making. Enter Spreadsheet Server from insightsoftware.