Data Engineering Vocabulary - Becoming A Data Engineer

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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.
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Пікірлер: 21

  • @SeattleDataGuy
    @SeattleDataGuy Жыл бұрын

    If you guys want to learn more about data engineering, then sign up for my newsletter here seattledataguy.substack.com/ or join the discord here discord.gg/2yRJq7Eg3k

  • @fox_trot
    @fox_trot Жыл бұрын

    Main of the vocabularies mentioned in this video. 1. CDC: capture data change 2. Normlization/denormalization 3. Pubisher/Subscriber AKA Producer/Comsumer 4. Execution plan 5. Data lineage 6. Data governance

  • @portabledata
    @portabledata Жыл бұрын

    Seattle Data Guy - Love the quick summaries of key concepts here! The pictures of the different types of normal forms are a great way to communicate the concepts

  • @SeattleDataGuy

    @SeattleDataGuy

    Жыл бұрын

    Glad it was helpful!

  • @TrijitSaha
    @TrijitSaha Жыл бұрын

    Crazy that you've uploaded this today having watched your previous video on this yesterday and binging your other data engineering videos in the last week. Love the content!

  • @SeattleDataGuy

    @SeattleDataGuy

    Жыл бұрын

    Thanks for all the support! Trying to keep putting stuff out! Actually at a conference right now so I am juggling a few things 😂

  • @txdba
    @txdba Жыл бұрын

    Thanks. Those were great topics to be prepped for when interviewed.

  • @ashraf7172
    @ashraf7172 Жыл бұрын

    How you are so great with your concepts. 😅 Inspiring us to work hard

  • @larryfisherman25

    @larryfisherman25

    Жыл бұрын

    I asked myself the same thing 😅

  • @boukraailyesali9131

    @boukraailyesali9131

    Жыл бұрын

    +9999999999999999

  • @SeattleDataGuy

    @SeattleDataGuy

    Жыл бұрын

    Thank you so much 😀 happy to help!

  • @idkwhy77
    @idkwhy77 Жыл бұрын

    thanks! Was interested in the field, still not in college so looking forward to it. Good to start early & prep for future :)

  • @ankursingh730
    @ankursingh7309 ай бұрын

    Love the content! Explanations are pretty simple which has really helped me understand few things. Thanks !

  • @SeattleDataGuy

    @SeattleDataGuy

    9 ай бұрын

    Great to hear!

  • @WarbossPepe
    @WarbossPepe8 ай бұрын

    Looking buff, boi!

  • @SeattleDataGuy

    @SeattleDataGuy

    8 ай бұрын

    hahaha thanks...

  • @thedailyepochs338
    @thedailyepochs338 Жыл бұрын

    Love the Ken Jee Merch

  • @Raviraj-1514
    @Raviraj-1514 Жыл бұрын

    Debezium is also a good example for CDC

  • @josipsadek4425
    @josipsadek4425 Жыл бұрын

    Hey, tnx for the video, love your content. You mentioned some links regarding the "Execution plan", but I can't find them in your description. Also, I would like to learn more about data governance, I am most interested in ensuring data we store is high-quality data. So any links are very appreciated. :) At my work, I learned that if a mobile app has any kind of bug and therefore analytics data is not collected properly, that incomplete data stays forever in our warehouse. So I would like to introduce some sort of system that makes sure that we store complete and high-quality data. Also, I would like to if the data is not complete that someone gets an email with details.

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