A Decade In Data Engineering - Has Anything Actually Changed?

Рет қаралды 9,280

Жыл бұрын

Data engineering as a job title has been around for a little over a decade.
In that decade we have seem massive changes occur in that 10 year span.
We went from Hadoop, to redshift to snowflake.
Airflow became popular.
And so much more.
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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.
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Пікірлер: 32

@SeattleDataGuy 11 ай 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

@minthura24 8 ай бұрын

Thanks for the video! Love your cats as well.

@SeattleDataGuy 6 ай бұрын

Thank you! she loves jumping in

@Soonicx1 9 ай бұрын

Holy shit this videos are really on point.

@SeattleDataGuy 8 ай бұрын

thank you! personally one of my favorites but i know its not for everyone.

@CrypticPulsar Жыл бұрын

This was very good content! Thank you

@SeattleDataGuy 11 ай бұрын

Glad it was helpful!

@josho225 Жыл бұрын

thank you for your content!

@SeattleDataGuy 11 ай бұрын

My pleasure!

@willemhekman1788 6 ай бұрын

Coming from someone switching from teaching physics at the moment (quantum physics / data science background) back into data aspiring to work as a data engineer, thanks for the clear overview (having now watched a few videos on the history).

@gavinkalaher7314 Жыл бұрын

Happy 10th dataversary Ben 🏆📆💪

@SeattleDataGuy 11 ай бұрын

thank you!

@UdiShvekey 2 ай бұрын

Wonderful summary. I really like your analysis and point of view! I agree with most of the stuff discussed here, and, to add my 2 cents, talking from a decade of experience plus plus... I think what we are seeing is more of the same... I even with the rise of snowflake and databricks, can't spot any real innovation or change. It is all just building on the same old tech. But perhaps the innovation should come from the actual organizations and their data strategies (which most of them simply don't have!)

@polloiaesthesis2525 Жыл бұрын

Your videos are really on point. The data industry is indeed always changing and it is hard for customers to keep with this pace of new releases. It is even harder to see the value you could get from implenting one of the new kid on the block in the data industry as many tools appear to fix issues of a former one, which is not really easy to sell to customers with tight budgets. Now there is all the fuze around data observability, but this adds more licences to the whole landscape without giving a clear ROI to customer who want to implement it. Where do you feel the industry will go to? More and more to a constellation of scattered solutions we need to inegrate and make work together or to the data platforms/fabrics that try to be the one-stop-shops of the data world? I personnaly think the latter will be predominant in the large enterprises but your input interest me a lot. :)

@SeattleDataGuy 11 ай бұрын

Thanks for the great comment, I probably need to make a video on this whole subject.

@thsstphok7937 Жыл бұрын

Hey Ben, I started learning data engineering some weeks ago. I'm loving everything and your channel is helping me the most. My only problem right now is the fear of using AWS and explode bills cost because of mistakes. I know it's possible set alerts or even scripts that are triggered by alerts to kill all resources but the fear don't go away. I'm learning and I know I will make mistakes, but what I can do to minimize the risks? Thank you!

@DroisKargva Жыл бұрын

Just forget about data engineering. It takes years to learn. I have been on thos roads for 1.5 year and still have no clue whats going on. There are too many technologies

@willi1978 7 ай бұрын

always migrating data since the stack continually changes

@SeattleDataGuy 6 ай бұрын

next year we'll all just be migrating data back on prem

@arslanarshad4801 Жыл бұрын

please provide full course of data engineer basic o advanced., thanks you

@user-bs8ku6cg9f Жыл бұрын

hey any palantir update? do you use the software or whats going on?

@1godfrey Жыл бұрын

Can you do a vid about migrating data from a traditional db to cloud (preferably snowflake)

@DroisKargva Жыл бұрын

Create a backup then take that and load it into cloud

@Kiesk_ Жыл бұрын

What is the summary?

@F00tball_Fan147 Жыл бұрын

Hello, my major is MIS, I want to become data engineer, I thought to start first as data analyst and work my way up to data engineer. What do you think?

@DroisKargva Жыл бұрын

Thats easy and right way to do it. Its super complicated to jump right into data engineering.

@hubstrangers3450 Жыл бұрын

presently there are loads of (> 80%) doesn't know how to write or extrapolate Hadoop, MapR and Hadoop ecosystem code, consider themselves to above "Engineers" or "Science" , "ML", "DevOp" or even "Developers" position, drawing more than whatever figure remuneration packages.......that's what's modern cloud companies have brought this sector, is it sad or progress, sorry the latest being ChatGTP's in the "ML" space......

@anildangol Жыл бұрын

What happened to color of your video? LOL

@SeattleDataGuy 11 ай бұрын

good question, maybe it was lighting....hmm

@paolocortez5358 Жыл бұрын

yep i don’t know how to do any of those and i am a data engineer. i’ll probably never need to know any of that information.

@DroisKargva Жыл бұрын

There are 2 types of data engineers: businessey data engineers and big data wngineers. In this video he mostly focuses on big data engineers requiring big data technologies like spark and hadoop. Anyhow I am with you

@polloiaesthesis2525 Жыл бұрын

@@DroisKargva This is an interesting distinction that I do not usually see in the market but would love to push forward. Do you think this vision is still valid with the Cloud Data Platforms that sell us the point that they can handle big data without Hadoop? Like Databricks, Snowflake, BigQuery or the new fabrics from Microsoft, SAP and Orcale?