Build with Us | Deep Dive: Building Your First Pipeline

hi today I'd like to step through one of palente tutorials available on learn. pal.com that tutorial is called Deep dive building your first pipeline rather than step through each step verbatim we're going to stick to the core workflow I'll leave the bulk of the reading to you by the end of this you'll have a pipeline deployed on your stack and you should feel comfortable navigating around the application and start feeling like you want to explore some of the more advanced features we'll point you at those Advanced features but they are out of scope for this training let's go ahead and get started okay here we are at learn. pal.com it's currently under the featured courses section building your first pipeline if you don't see it here however use that search bar in the upper right you can search for it by keyword the course will pop up click take course and here's what happens you get the agenda here are all of the modules within this training that we're going we are not going to open every single one of these some of these are uh give you info that's going to help you complete the training get the training that you need about this course we'll review the learning objectives things that you should know or have practice with once you're done with the the training there are just a couple things I'm going to call out from the overview and setting up your project and folder section here first here 's an image from the introduction section a pipeline and Foundry is a series of input data sets or data set that's transformed in some way to generate an output data set or data sets those outputs can in turn be used as inputs to the next segment of the pipeline and that can continue until you are left with a series of data sets that support your workflow pipelines are built in service of something in Foundry sometimes they might be built to structure a data set so that it can be ready for analysis if might be to shape a data set so that it can back an ontology object type maybe it's to be used as an input to a model regardless when data lands in from a raw Source typically needs to undergo some kind of cleaning preparation exercise enrichment exercise in order to make it ready for whatever it is we brought it into Foundry to do in the first place