We actually use it for building out some rough incrementally, slowly changing dimensions sometimes in certain situations. It’s definitely great for executing any type of sequel or short procedures on any type of frequency. I think we’ve got some links in here for you guys to check out that topic but right now it’s going to drill down on task. We’ve set up streams and there are tasks right there and we’ve got an upcoming topic on Snowflake streams. I can’t remember really seeing it disconnected anytime. It’s really I wouldn’t even say a compliment or I would say it’s a counterpart to Snowflake streams or table stream. So it has a lot to do with Snowflake clearly and if you look at the definition of a task, it’s really a piece of work to be done or undertaken. You’ve got streams and tasks are kind of part of that framework, if you will. Tasks currently if you’re using actually any part of the Snowflake data pipeline and I consider the data pipeline really anything at the point of ingestion into Snowflake and doing any type of transformation or logic and I consider task as part of that data pipeline. I’d love to hear from, loves to hear if you guys are using. And if anybody has any questions, of course fill the questions into the chat. And so let’s hit on some of the general purpose and power of Snowflake tasks. So we like to just kind of drill down into some specific topics.Īnd tonight’s topic is about Snowflake tasks. And we can talk Snowflake and its internals and its power all day long, but it needs to meet up. So that is kind of Snowflake in a very, very quick nutshell. And they’re running into that funnel of ELT and ETL to get meaningful information out of their data, create insights and that types of things from all different types of consumption layers, whether it be machine learning, business analytics and so forth and so on. It solves a lot of different problems across a lot of different industries, vertical and definitely horizontally across the enterprise.Īnd we have customers and we know people who are ingesting all types of data that you wouldn’t even think about off the top of your head. We like it, we recommend it, we think it’s great. Kind of the world’s answer to doing data warehousing on the Internet right now. Very powerful, almost infinite scale, very fast processing. Again, keep this super short for everyone coming back in. There’s a link and we send out the slides, guides and the link to the YouTube video once we have it posted for everybody. And for those who ask the question, we do have the recordings of all these meetups available about one to three days after we have it.Īnd they’re all posted on our YouTube AICG channel. The VTA, I think it is from that show, really cool show if you haven’t watched it. And so speaking of our last meet up, yes, if you’re fans of the Disney Loki and you’re part of that meeting last time, we talked a lot about variance and the time authority. So just replace everything you see there with variants, which was our last meet up with tasks from this meet up. I thought we changed it, but we’re really going to be talking about tasks and very similar concepts. And of course, follow us on Day Lake House on LinkedIn and Twitter. So I’m hoping that in this session we can kind of elucidate and kind of clarify some of the misconceptions and also talk about some of the powerful uses of text.Īs always, meet up rules, just be kind, participate and videos optional. And we’ve been using them for a while on lots of different projects, but I don’t remember when it was incarnated, to be honest.Īnd lots of people I find who are coming just from a pure SQL background, they’re not sure how to even use them, maybe still get ETL and there’s some confusion. I don’t remember when they came out with tasks, actually, to be honest with you. I’d love to hear everybody’s input and feedback if they’ve used tasks before and that type of thing. So we’re going to just kind of walk through that. There’s a task object in Snowflake and we call them task collectively. Just like there is a table object, so you call them table. And well, actually it’s a Snowflake task. In general the relationship needs to be formed as embedding if the data needs to be queried together to form a single view in your application.Welcome to another Carolina Snowflake meet up session and today we’ll be talking about Snowflake tasks. The cool thing about MongoDB is its flexible schema and the ability to use an outlier pattern for some extreme use cases in your app.
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