Okay let's run through two quick use cases and then I really want to get you started within Google cloud platform itself. So I'm going to do a quick tour of that. I'm going to set you up with your sandbox accounts and then really get you into BigQuery and other tools to get you started. So let's run through these examples pretty quickly. First was a cool UK company that I found that was using Google cloud platform called Ocado. If you're not familiar with them, they are a very large online grocer inside the UK. And they basically turned to a Google Cloud platform, BigQuery in particular, when they said, wow, we're processing sheer massive amounts of data to handle all these online grocery transactions in addition to the actual transactions. We need to pipe all that transactional data and all of the weather data and all of our distribution data into some central analytics reporting warehouse. Where we can just store it all there and then operate very, very quickly in an ad hoc analysis basis and query that data very quickly. And not have to worry about building this massive infrastructure ourselves. And that's exactly what they turned to BigQuery for. Is storing that data and then write these kind of analytical queries and get those insights back really, really quickly. Another example is Spotify, which is a music streaming service and a whole music experience service. And they turned to Google Cloud platform and BigQuery in particular to basically, the same argument that we hear time and time again. Is, you can spend your time as a data analysis, as a data scientist, on really thinking about those cool insights and those queries that you want to write, as opposed to managing for hardware failure or redundancy or backups or anything like that. If you're a data engineer and that's your core job, more power to you. That's super fun and those jobs are definitely necessary, and Google itself has droves of engineers that make the platform, the service of BigQuery, happen. But if your goal is to glean insights for your business, perhaps better spent to write those awesome queries, and spend your time on thinking of more ingenious ways to tease insights out of your data than worrying about that infrastructure.
