Відео

DBA skills still valuable, adapt or perish.

Cloud is king, upskill for data roles.

Surfalytics helps navigate career changes.

Top as usual

Thanks. Still see this role when searching for a job.

DBA has lots of valuable skills to become DevOps or Data Engineer.

"Every failure is a big sucess" 😁 Such an inspiring way to reframe challenges into opportunities!

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Very informative content. Thanks a lot for creating the content. If possible can you provide a direct download link for this mind map. Thanks in advance

Data modelling is fundamental knowledge for any data profession.

Your video was exactly what I needed. Thanks for the clear explanations you provided and the links!!

I appreciate the comparison between different approaches and the focus on real-world applications.

Thanks, Dmitry, for breaking down data modeling in such an understandable way.

Dmitry, you mentioned a few time in the video about "tech dept". Could you, please, tell about it more?

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It is the only UA-cam author I watch every video. The concentration of REALLY useful information is enormous. Thank you!

The content quality is excellent; I’m looking forward to more videos. Thanks!

15:39 There is a mistake in the logic of the written solution. In general, if there was no situation when one customer can make two orders in one day, it would not matter what to use - dense_rank, rank or just row_number, because we use it only to order the orders (sorry for the tautology) by date. And then it will be the same order_number value for different products in one order (due to unification by order_id) thanks to the join. But the code that is shown on the screen does not work and does not provide for the edge case of two orders of one customer on the same day, where each order has two products. The current code will not distinguish between two orders and will output one value in the order_number column. This will happen because the table that is considered in the CTE will have a window function only in the customer section and ranked by order_date. There are two ways to fix this bug: 1. either change dense_rank to row_number - then we will simply make a sequential number for each order by order_date and then during the join we will get the required value for the products: row_number() over (partition by customer_id order by order_date) as rn 2. or add "order_id" to the existing expression "dense_rank () over (partition by customer_id order by order_date) as rn" to get the expression "dense_rank () over (partition by customer_id order by order_date, order_id". Then the orders_rank CTE table will have the correct sequential numbers for orders, which will then be joined to the final table. But if we want to make ranking without CTE, then we should simply use the second option with dense_rank and then we will get: select po.customer_id, p.name, dense_rank() over (partition by po.customer_id order by po.order_date, po.order_id) as order_number from purchase_order po left join order_product op on op.order_id = po.order_id left join product p on p.product_id = op.product_id order by po.customer_id, dense_rank() over (partition by po.customer_id order by po.order_date, po.order_id) If you are interested, you can try to do it yourself in the sandbox that I created. You need to pay attention to orders numbered 31 and 32: sandboxsql.com/e914bc1b-d312-4e96-841c-cf055505324d Thanks for the content and the opportunity to sit and dig into the task!

I would add that the growth rate in the 3rd task should be calculated a little differently: not by simply dividing the current period by the previous one, but by subtracting the past from the current one and then dividing by the previous period. Otherwise, thanks for the video:)

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Totally agree about growth mindset

AI is so cool, so many things can be done faster thanks to AI. But it's just a tool.

Thank you for sharing your insights. I feel much more at ease and reassured after hearing your thoughts.😁

Great video. All about mindset.

Sports and exercises are important!

I appreciate your honesty about the current limitations of AI. It's refreshing to hear a realistic take.

Great perspective on the future of data jobs, Dmitry! Thanks for sharing your insights.

The growth mindset message is so important! 🙌 We should all focus on continuous learning.

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Thank you.

I heard that cloud computing growth stoped or even starts to fall down. Is it true?

Looking forward to the hands-on projects! 🛠

Will we be covering any specific cloud certifications in this module?

Cloud knowledge is important like Microsoft Office 20 years ago.

I’m curious, will you be addressing the comparison of cloud computing services and how a company decides to choose one vendor over another?

Hi Dimitri @SurfalyticsTV First of all, thank you for this video series. The information you provide is invaluable. Not only is it helpful for interviews, but it’s also highly beneficial for data architects. I have a question in mind that you might consider addressing in a future video. How do you determine the appropriate cluster size (whether it's EMR, Databricks, or any Spark-based compute) when processing petabytes of data daily in batch mode?

Can't wait to get hands-on!

Can't wait to see the next video and dive into these concepts! Your content always makes learning so exciting!

Excited for Module 4! 🚀

Ready to level up my skills! 💪

It is windy!

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Great job!!!

Great video, Dmitry! Go on!

Looks great, hopefully I'll be attending to this annual gathering in Tofino next year.

Weather was nice!

Great intro! I'm interested

Looking forward to joining your camp in Tofino next time!