Systems | Development | Analytics | API | Testing

Are your marketing dashboards telling you what happened—but never why? Campaigns are underperforming, budgets are under scrutiny, and every answer seems to require a ticket to the data team. ThoughtSpot CMO, Micheline Nijmeh, just went hands-on with Spotter—the AI analyst built for marketers who need answers now, not next sprint. Spotter doesn’t just chat. It investigates your toughest marketing questions so you can move from guesswork to confidence: Why did pipeline drop this week?

Stop manually wrangling data and start automating your governance. In this technical deep-dive, we explore how to leverage ThoughtSpot Modeling Language (TML) to manage complex joins and enforce strict business rules at the architectural level. Traditional UI joins are great, but sometimes you need to ensure end-users only interact with a specific subset of data—like active subscribers—without giving them the ability to toggle filters. By moving your logic into TML, you create a "Join with Filters" that hardcodes business rules directly into your data model.

Struggling to figure out why your sales reps are underperforming? Zorana, a Sales Manager at Databox, walks through how she built a dashboard that connects activity, conversion, and revenue — all in one view. See how she identifies who needs coaching (and why) Learn how she makes data-backed decisions each week Discover how Databox helps turn sales data into action No more guessing. No more gut feelings. Just clear visibility into what drives performance.

LinkedIn Ads only show 25 companies in their reporting. But if you’re running demand gen for B2B clients, that’s not enough. In this quick walkthrough, Jason Spooner (Founder, Jars Digital) shows how he uses Databox to get a complete view of LinkedIn ad exposure by company—so you can: See every company engaging with your ads Match ad data to pipeline and revenue Prove marketing’s impact on sales Whether you run paid media for clients or in-house, this tip helps you unlock more insight and drive better decisions.

Andy Steinmann of MarketAxess walks through how his team learned that “managed” Apache Kafka wasn’t really managed—and why Confluent Cloud was different.