Systems | Development | Analytics | API | Testing

Fix Your Sales Forecasting: How Databox Uncovered Real Win Rates

Tired of inaccurate forecasts and one-size-fits-all coaching? Tory Ferrall from Databox shares how her team revamped their sales forecasting model to drive better results—using Databox to calculate real win rates based on actual deal stage performance. By tracking when deals enter each stage and analyzing their true conversion likelihood, the team identified gaps that HubSpot’s default probabilities missed. The result? More precise forecasting and deeper insights for rep-level coaching.

How to Run QBRs Like a Pro: One Dashboard, Full Customer Journey

Quarterly Business Reviews don’t have to mean juggling six different reports. Cameron Collins from RevPartners @revpartners1459 shares how he uses Databox to deliver executive-level QBRs that showcase the entire customer journey—from first web visit to closed-won revenue. By combining cross-object metrics like average deal size, funnel conversion rates, and revenue trends into one cohesive dashboard, Cameron helps leadership teams quickly identify bottlenecks and drive smarter, data-backed decisions.

Stop Building Useless Dashboards: How to Do Sales Attribution Right in HubSpot

Most dashboards suck. Not because the data’s wrong (though it often is)—but because they’re not built to answer real business questions. Crispy Barnett at Supered (@GetSupered) shows you how to report like a rockstar inside HubSpot, starting with sales attribution that actually drives decisions.

insightsoftware Data & Analytics | Reporting, Dashboards, AI Insights

@assignees please use this: insightsoftware Data & Analytics | Reporting, Dashboards, AI Insights The insightsoftware Data & Analytics platform helps you connect, prepare, and analyze data across your organization. It supports everything from governed reporting and operational dashboards to self-service analytics and AI-powered insights.

From Data to Insight Activation: Key Takeaways from Data Summit 2025

Every year, Data Summit attracts data professionals to Boston for three days to exchange ideas and innovation. In 2025, the event was dedicated to data management trends, Big Data, business intelligence (BI), analytics, as well as emerging innovation in AI and machine learning. At the Data Summit, Sami Akbay, insightsoftware’s Head of Data Analytics Projects, hosted a session on the evolution of BI, the rise of generative AI, and the shift toward insight-driven workflows.

Why CFOs Need Connected Solutions Now More Than Ever

The evolving market landscape is driving an urgent need for a unified enterprise performance management (EPM) solution, as finance teams face increasing pressures from several fronts. Rapid technological advancements, heightened competition, and the growing complexity of global markets have made financial agility and real-time decision-making critical to maintaining a competitive edge.

Part 2 - "Hello World" - Integrate Qlik Automate with Qlik Cloud Analytics

"Hello, World" — the training wheels of learning. It’s the simplest proof that you’ve taken your first step—and from there, it gets addictive fast. Now, speaking of first steps... Part 2 of "Taking Action on Your Data" is live! In this video, we dive into how to connect your Qlik Analytics Apps to a Qlik Automate workflow—an easy win to start taking action on your data.

Unlocking Real-Time Analytics on AWS With Tableflow, Apache Iceberg, and the AWS Glue Data Catalog

In today's competitive landscape, data warehouses and data lakes are the essential platforms for business intelligence, analytics, and AI. While immensely powerful, these systems were traditionally designed for batch data processing, often leading to insights based on data that is hours or even days old. The primary challenge has always been the complexity of bridging the gap between real-time data streams, typically flowing through Kafka, and these analytical systems.

Dual MCP Support in Astera AI: What it is and Why it Matters

Enterprise automation didn’t start with AI agents, but they’ve had a much bigger impact than earlier automation methods, such as software scripts or bots. Modern AI agents can do a lot more than tackle repetitive tasks. They can reason through complicated workflows, choose the best course of action, and access tools to execute said action. But to do all this, AI agents require interoperability. They need to be able to connect to numerous tools, databases, services, and APIs.