How an AI Assistant Can Work With Your Business Data with MCPs

And instead of getting a generic answer or being told to check your dashboard, the AI pulls the exact numbers from your company’s data and gives you a real answer in seconds. This is no longer science fiction. A new technology called MCP (Model Context Protocol) makes this possible. It’s a standardized way for AI tools to securely connect to your business intelligence and analytics platforms and actually work with your real data.

How to Replace Your Retired Microsoft Access Salesforce Connector

Microsoft officially retired the built-in Salesforce ODBC connector in Access on October 28, 2025 for Microsoft 365 monthly versions and November 11 for semi-annual and perpetual licenses. Teams that relied on Access for quick Salesforce data pulls, lightweight reports, and dashboard connections suddenly found their Microsoft Access Salesforce connection not working. Here, we discuss what happened, who’s affected, and how to get your data flowing again with minimal disruption.

What is Headless BI? A Guide for Leaders Who Need Answers, Not Just Dashboards

You have more data than ever, but getting a simple answer feels impossible. Your data lives in dashboards you can’t question and reports that are outdated the moment they’re published. You’re paying for analytics tools that most of your team never touches. And when you actually need an answer – in a meeting, on a call, right now – you’re told to wait for someone to pull a report.

Streaming Data Integration with Apache Kafka

Data streaming with events supports many different applications and use cases. Event-driven microservices use data streaming, allowing companies to build applications based on domain-driven designs. This approach allows teams to break applications into composable microservices that can be worked on independently, speeding development. These designs scale well and can process huge amounts of data efficiently.

Qlik: Making Data Work for AI

AI is moving fast, but outcomes still depend on one thing: trusted data, in the right place, at the right time, with the right controls. In this short Qlik story video, you’ll see how we help teams accelerate AI with confidence, turning data into answers you can explain, and actions you can stand behind. From strengthening supply chain decisions, to building a campaign plan in seconds, to spotting changes as they happen, Qlik connects analytics, automation, and governed AI experiences, so AI becomes operational, not experimental.

Making Data Work for AI

AI is not a pilot anymore. In 2026, it is the operating agenda. And if you’re leading a business or an IT project right now, you’re probably getting the same two questions. First: “When do we see real outcomes?” Second: “Can we trust what we’re getting?” Those are fair questions. They’re the right questions. Because the truth is, the model is rarely the problem. The hard part is everything around it. The data. The access. The silos. The controls.

Building for Agentic AI

Our customers’ worlds are complex, and for good reason. It’s multi-cloud. It’s SaaS plus on-prem. It’s Snowflake, Databricks, AWS, Azure, Salesforce, and more. Underneath every one of those choices is the same constraint: data must be accessible, stay current, and stay controlled. The hard part is getting trusted data where it needs to be, when it needs to be there, with the controls to use it responsibly.

Capturing User Logins for Business Intelligence Insights with ThoughtSpot

Bridge the gap between deploying analytics and driving actual adoption by capturing and analyzing real-world user login behavior. In this technical walkthrough, we explore how to utilize ThoughtSpot CS Tools to extract audit logs and activity data, giving admins and stakeholders clear visibility into platform engagement. In this video, you will learn how to: The Result? A data-driven approach to platform administration that replaces intuition with hard evidence of user adoption and engagement.