#data engineering

[garyowl]

Sycophantic AI: Why Language Models Flatter Users Even In Neutral Queries

Explore "Sycophantic AI: Why Language Models Flatter Users Even in Neutral Queries" and uncover the alarming trend of AI's excessive flatter

[dkettchen]

absolutely unintelligeable meme I made during bootcamp lecture this morning

[seenivasan]

Data Engineering Syllabus | IABAC

This image displays a syllabus for data engineering. Big data, cloud platforms, databases, data warehousing, ETL, programming, data pipelines, data modeling, real-time processing, and data security are some of the subjects covered. These subjects are key for developing data engineering skills. https://iabac.org/blog/what-is-the-syllabus-for-data-engineering

[raindoor]

Thank you, AWS Glue job, for taking 8 minutes to tell me that you failed because I forgot to import a Python module. That's something that running the same Python script from command line would have told me in half an eyeblink.

[algo2ace]

🚀 Exploring Kafka: Scenario-Based Questions 📊

Dear community, As Kafka continues to shape modern data architectures, it's crucial for professionals to delve into scenario-based questions to deepen their understanding and application. Whether you're a seasoned Kafka developer or just starting out, here are some key scenarios to ponder: 1️⃣ **Scaling Challenges**: How would you design a Kafka cluster to handle a sudden surge in incoming data without compromising latency? 2️⃣ **Fault Tolerance**: Describe the steps you would take to ensure high availability in a Kafka setup, considering both hardware and software failures. 3️⃣ **Performance Tuning**: What metrics would you monitor to optimize Kafka producer and consumer performance in a high-throughput environment? 4️⃣ **Security Measures**: How do you secure Kafka clusters against unauthorized access and data breaches? What are some best practices? 5️⃣ **Integration with Ecosystem**: Discuss a real-world scenario where Kafka is integrated with other technologies like Spark, Hadoop, or Elasticsearch. What challenges did you face and how did you overcome them? Follow : https://algo2ace.com/kafka-stream-scenario-based-interview-questions/

#Kafka #BigData #DataEngineering #TechQuestions #ApacheKafka #BigData #Interview

[datascienceunicorn]

https://towardsdatascience.com/enterprise-ml-why-getting-your-model-to-production-takes-longer-than-building-it-e44ef80f8969

Enterprise ML — Why getting your model to production takes longer than building it

The complexities of model deployment, and integrating the application/data pipeline. What the Data Engineer, ML Engineer, and ML Ops do.

HT @pivigo #datascience #MLOps

[datascience-from-the-trenches]

Data science interviews dropped by 15% in 2020 while data engineering interviews increased by 40%

Source: https://finance.yahoo.com/news/data-science-job-market-shrinking-122300456.html

Data Science Job Market Shrinking as Data Engineering Grows Exponentially, New Study by Interview Query

Data science used to be the sexiest job of the 21st century. Now, the pandemic has cooled it down dramatically. Data science growth slowed d