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Vocabulary for Data Engineers - Data Engineering 101

There is a lot of jargon we throw around as data engineers. Data warehouse, data lake, data pipeline, ETL, ELT and more. But what do all these terms mean? What is a DAG? What is IPaas? And what role do they play in our data engineering world. Does your team need help getting up to speed on what is going on in the data world or do you need help setting up your data strategy, then set up a free consultation with me! https://calendly.com/ben-rogojan/cons... If you enjoyed this video, check out some of my other top videos. 0:00 Intro 0:30 What Does DAG Mean? 1:38 Data Pipelines, ETLs, ELTS , IPaas 4:40 Data Warehouse and Data Lake 7:51 What are Fact and Dimension Tables? 9:40 What are Slowly Changing Dimensions? 12:41 What is an SLA? Top Courses To Become A Data Engineer In 2022    • Top Courses To Become A Data Engineer...   What Is The Modern Data Stack - Intro To Data Infrastructure Part 1    • What Is The Modern Data Stack - Intro...   If you would like to learn more about data engineering, then check out Googles GCP certificate https://bit.ly/3NQVn7V If you'd like to read up on my updates about the data field, then you can sign up for our newsletter here. https://seattledataguy.substack.com/​​ Or check out my blog https://www.theseattledataguy.com/ And if you want to support the channel, then you can become a paid member of my newsletter https://seattledataguy.substack.com/s... Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio _____________________________________________________________ Subscribe:    / @seattledataguy   _____________________________________________________________ About me: I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data. *I do participate in affiliate programs, if a link has an "*" by it, then I may receive a small portion of the proceeds at no extra cost to you.