TechnologyAdvice’s Post

🚀 Exciting News! 🚀 We're launching 30 𝐃𝐚𝐲𝐬 𝐨𝐟 𝐃𝐚𝐢𝐥𝐲 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐍𝐮𝐠𝐠𝐞𝐭𝐬—a journey packed with tips and insights on Data Engineering! Stay tuned and don't miss out! 🔔 Turn on your LinkedIn notifications and follow us on Twitter to catch every post. Get ready to elevate your data engineering game! 🌟 Join our vibrant Data Engineering Community (DEC) below: 🔗https://lnkd.in/dwe4Z-V6 #30DaysDENugget #Dataengineering #Data #Analyticsengineering

Did my initial reading of the paper we want to implement. As data engineers, we don't read this too carefully since this is written for data scientists. We are just trying to scope out the battlefield... This looks pretty cool, and a successful implementation would be a huge powerup vs our last image embedding experiment, which basically allowed us to do only image search (albeit very accurate search across 6 bands). Text + image search would be awesome and I am sure our pretend customers would really enjoy functionality like this in our pretend product. Let's fork this repo, fire this puppy up, and poke around! Ideally, we should have something we can integrate with our favorite vector database, Pinecone.

Data Council #conference is NEXT WEEK!! 🙌 🙌 🙌 A bunch of the team will be there to support Iaroslav Zeigerman in his #talk: Evolving #data #pipelines at Scale! 📈 📆 Tuesday (Day 1 of the conference) 4:45 pm It's going to be a great #technical talk about some of the core principles around #SQLMesh https://lnkd.in/gA5bTMeB #excitedtolearn #dataops #sql

To reflect the ever-changing job market we've added some jobs to our #dataroundup in addition to the awesome data news and articles we curate for you and the community on a weekly basis 💼 👉 Cannibalisation in the Data Stack by Julien Hurault 👉 Some great roles from Cognify Search Harry Gollop 👉 Latest Youtube vid from Seattle Data Guy; why and how Data Engineers can review their data quality strategy 👉 Incredible deepdive into the inner-workings of Snowpipe by Yuval Itzchakov. Highly recommend this one Check it out below!! https://lnkd.in/en3GJvBB

🤣 How to Ruin a Data Engineers Day (in 20 Easy Steps) New Article by Tim Webster https://lnkd.in/ezpVfF9h - - - - - - - - - - - - - - - - - - - - - - - - - - - 💡 Follow for more great content! ✅ ✍️ Want to contribute? Connect with us. 🔗 Let's create together! ✅ - - - - - - - - - - - - - - - - - - - - - - - - - - - #dataengineering  #dataanalytics #careerdevelopment #careeradvice

"Building a FastAPI Service Quickly and Efficiently" If you're interested in learning how to set up and optimize a FastAPI service, check it out! I dive into best practices and my experiences as a data engineer.

Get ready to navigate the data landscape with Harun Mbaabu Mwenda at #GoogleIOExtendedMtKenya! He'll be delivering a keynote "Excelling in Your Data Career: Rising Above the Noise". He'll share invaluable insights on how to excel in your data career. Don't miss this chance to network with fellow data enthusiasts and gain practical knowledge.

❤️ To the Data Engineer: You Don't Need to Master It All 💡 Article by: Tim Webster ➡ Link to Article: https://lnkd.in/dVDa2erf - - - - - - - - - - - - - - - - - - - - - - - - - - - 💡 Follow for more great content! ✅ ✍️ Want to contribute? Connect with us. 🔗 Let's create together! ✅ - - - - - - - - - - - - - - - - - - - - - - - - - - - #dataengineering #datascience #careerdevelopment #dataanalytics

Always underestimate your ability and the ability of others to understand what you were thinking when you wrote your code 😂 Write code comments! ✅ Take care of future you. ✅ You’ll make other future users of your code happy too! 🧙♂️ Thoughts? - - - Follow, connect, and share your perspective! 📚 Visit the link in my bio for more content and free resources! #data #analytics #dataanalytics #dataanalyst #datascience

Being a data engineer, I have seen a million queries. I have a guideline for how long something should run or not. ⌛ If a query runs for more than 2 minutes, then I've made a mistake somewhere. Should I need to use it more than once, I'll cancel, investigate, and fix it. Even for a single use, there are extremely few exceptions for when something should run for more than 5 minutes. I could simply list a bunch of steps, but there are a couple of principles guiding my approach: * using the least amount of data is the fastest * using meaningful grain helps to debug In reality, both are about speed - the first one is the running/execution speed, and the second one is the reading/writing/comprehension speed. Combine both for bonus points :) It will be a series of about 15 posts over the coming weeks. If this seems interesting, then hitting "follow" is an easy way for them to show up in your feed 🙂