Systems | Development | Analytics | API | Testing

Reliable Pipelines, Predictable Bills: Why Settle for One Without the Other

Somewhere along the way, data teams accepted a trade-off: pipelines that just work, or bills that you can actually forecast, pick one. So you live with the silent failures, the schema changes that break dashboards overnight, and the month-end invoice that never quite matches the data you moved. Not because it's acceptable, but because it's familiar. In this session, we're challenging that trade-off head-on. We'll break down where pipelines fail quietly and where costs inflate invisibly and show you, live, what it looks like when your pipeline gives you full visibility into every sync, every record, and every dollar.

How to Load Data From Facebook Ads to BigQuery (3 Proven Methods for 2026)

KEY TAKEAWAY Facebook Ads data drives your campaign decisions, but Ads Manager makes it hard to analyze that data at scale or combine it with other sources. Moving it into BigQuery fixes that. Once your ad data sits next to your CRM, product, and revenue numbers, reporting becomes faster and cheaper across all of it. There are three ways to get there: Automated ETL with Hevo: best if you want fresh data without the upkeep. Custom code: best if you have engineers who want full control.