tl;dr In this session we will demonstrate how you can expose any amount of data from BigQuery as low-latency APIs with Tinybird in two different ways:- extracting directly from BigQuery at regular intervals, or - streaming the data constantly via Google. DataflowBigQuery is not designed (or priced) to withstand hundreds of requests per second. And yet, all of that analytical data you may be gathering in BigQuery holds great value to your customers as well, not just to you. Making the results of your insights available to your customers can be a key differentiator. Product companies are waking up to this: stats around each user’s activity (In-product analytics) can provide invaluable insights to those very same users. Other times it can help them quantify the value you are actually providing.
Take The Hotels Network, for instance, one of our favourite customers. Their core business is to improve conversion rates & personalisation on hotel reservation websites by running predictive analytics. However, it is key for their customers (the hotels) to be able to understand in detail how and why conversion rates are better: that’s why each of the hotels can access analytical dashboards that The Hotels Network makes available to them. However, exposing all of that data as soon as it is available (the more up to date it is, the more relevant and valuable), with low latency (nobody likes slow charts) and to potentially many customers at once, comes with its own set of challenges. In this session we will explore how to create fast APIs over your BigQuery datasets in a matter of minutes. Sign-up to watch live or if you want to receive the recording!
Learn how to build a quick and easy API endpoint using open data. It will not take you more than 10 minutes!