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Change Data Capture with Google Analytics
Introduction Let’s pretend you work at a small identity protection startup and you’re getting acquired by a Fortune 100 corporation. You and 120 of your peers are waiting on huge acquisition checks, the champagne is on order, and there’s palpable, anxious excitement in the air. Morale is high and you’re all ready to join the big leagues. There are nervous smiles everywhere you look and you’re waiting to go on a hiring spree to start scaling. You’re feeling good… Until an email comes in from the acquiring corporation’s security and compliance group. You’re being asked some intense questions for
Introduction Imagine that you’re the analytics team lead at an e-commerce company. Your company has seen rapid growth in the last few months, with thousands of new users who are highly engaged on your website. Your leadership team is pushing for the analytics team to dig into user activity data that has been carefully collected inside your production database to figure out how to make your website’s experience even better. Excitedly, one evening you spin up a data warehouse and set up data connectors to replicate data from your database into your data warehouse. The next morning, you wake
3 Layer Framework
Introduction How do you think about your data stack? If your job requires analyzing data, or supporting teams who analyze your data, you will likely find yourself at some point working on data pipelines and learning about their complexity as you go along. While data pipelines are light years ahead of where they were 20 years, the day-to-day challenges data teams face today are largely the same. How have we come so far, yet stayed where we are? We have seen tons of thoughtful work being done to promote the modern data stack. Andreessen Horowitz’s seminal thought piece on

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