Data engineers share their biggest on-the-job frustrations, from battling organizational silos and cleaning messy human-entered data to the soul-crushing 'work about the work' caused by tool sprawl. Discover the real challenges that go beyond the code.
Exploring the real-world viability of synthetic data for LLMs, with insights on fine-tuning smaller models, tackling latency, and resources for practical application.
Developers share their go-to tools and techniques for cleaning and transforming data before imports, highlighting the power of scripting, challenges with common tools, and best practices for a robust data pipeline. Discover insights on managing everything from date formatting to complex code mapping.