Azure Data Factory, Azure Databricks, or Azure Synapse Analytics? When to use what. - Lisa Hoving

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  • Опубліковано 4 жов 2022
  • Presentation from Sytac Azure Night www.meetup.com/sytac-dev-jam/...
    Have you ever found yourself at the start of a data (engineering) project, unsure about what tool to choose? Speak no more! In this session we will discuss three often used (data engineering) tools on Azure:
    - Azure Data Factory
    - Azure Databricks
    - Azure Synapse Analytics
    First, I will give a brief introduction to each tool, including for what use cases they are commonly used. Next, we will talk about what makes these tools different, and where they overlap (and believe me, they do). Lastly, we will arrive at our conclusion: when to use what. Of course, a slide on differences in costs will be included as well.
    Lisa is a friendly Data Engineer from the neighbourhood. Her background comes in Finance, but she has had the pleasure to be working in IT for the past 5 years. At Intercept, she helps customers in migrating their data applications to the Azure cloud.
  • Наука та технологія

КОМЕНТАРІ • 20

  • @TeferiHagos
    @TeferiHagos 7 місяців тому +1

    One of the best UA-cam videos I have ever watched. Now, I understand the difference between these 3. Great job, teacher!

  • @jyotirdas6326
    @jyotirdas6326 День тому

    very nicely explained , thankyou so much...

  • @geojbarros
    @geojbarros Рік тому +2

    I did love your explanation about the differences between these three environment, Lisa. It clarified a lot of doubts that I had in my mind about it. Thanks a lot.

  • @carloscantu75
    @carloscantu75 Рік тому +1

    Just the content I was looking for, thanks for sharing in such a clear and concise way!

  • @datacraftersrd970
    @datacraftersrd970 Рік тому +1

    Awesome explanations. Thanks, Lisa Hoving

  • @jackmaguina8480
    @jackmaguina8480 Рік тому +1

    Well donde. Thank you Lisa

  • @demirel16
    @demirel16 Рік тому +1

    Great presentation. Thanks

  • @wasimx6707
    @wasimx6707 Рік тому +1

    Thank you for sharing It really helped me to understand the difference between these 3 ☺️☺️

  • @chandrasekhar1883
    @chandrasekhar1883 Рік тому +1

    Very helpful. Thank you so much

  • @srinathp4486
    @srinathp4486 9 місяців тому +1

    thank you lisa from india🙏

  • @theitpro4688
    @theitpro4688 Рік тому +1

    nice course

  • @bijosn
    @bijosn Рік тому +1

    Hi, my name is Henk, nice to meet you

  • @davidk4682
    @davidk4682 Рік тому +1

    Thank you Lisa, that was essentially a master class on the differences. Excellent. How does Snowflake compare? (separate video probably and also depends on the use case of course). Thank you again for this information. Job well done.

  • @dans4786
    @dans4786 Рік тому +1

    Isn't it true now that it's not necessary to know Spark for Databricks? I thought the transactional layer abstracts away the need to write Spark code and instead provides options to use SQL or Python.

    • @LisaHoving
      @LisaHoving Рік тому +2

      Hi Dan, in many ways, you can view Apache Spark as a package. We can program it with Python, Scala, and many other languages. So, even though you can program Python in Databricks, just Python is not enough, unfortunately. We also need the powers of Apache Spark! However, if you already know Python, Apache Spark is just onee step away :)
      And, even though it's technically true you can program SQL in Databricks, I do find that the SQL language by itself does not offer enough flexibility for most use cases. But, to be fair, some people are much more handy with SQL than me, haha!

  • @EMoscosoCam
    @EMoscosoCam Рік тому

    What about using a VM with SSIS inside? Thanks.

  • @saktibiswal6445
    @saktibiswal6445 10 місяців тому +1

    Isn't Intercept a pharma company?

    • @LisaHoving
      @LisaHoving 9 місяців тому

      it's a Microsoft partner 😄

  • @dans4786
    @dans4786 Рік тому

    Isn't it true now that it's not necessary to know Spark for Databricks? I thought the transactional layer abstracts away the need to write Spark code and instead provides options to use SQL or Python.

    • @artus198
      @artus198 8 місяців тому

      I think Spark is very similar to python in Syntax... I think people use a combination of Spark and SQL in a given Notebook in Databricks.