Why Is It So Hard to Make Data Useful? | Modern Data Engineering Pipelines
More: https://developer.confluent.io/ | Why do organizations spend $12.9 million annually on poor data quality while data engineers waste 80% of their time cleaning up messy data? Despite generating 480 million terabytes of data daily, most organizations struggle to extract meaningful insights from their information. This video reveals the hidden challenges in the data engineering lifecycle and the critical trade-offs that determine whether your data becomes a competitive advantage or an expensive liability. You'll discover why real-time data often gets converted to slow batch processes, how to balance monolithic versus modular architectures, and when to prioritize data freshness over queryability. We'll explore the complete data engineering lifecycle through four key stages - generation, ingestion, transformation, and serving - and examine how each stage presents unique challenges and trade-offs. You'll also learn about the Medallion Architecture's Bronze, Silver, and Gold layers, and understand when to choose streaming versus batch processing for maximum business impact. Technologies covered: Apache Kafka, Data Warehouses, Data Lakes, Data Lakehouses, APIs, ETL/ELT pipelines, Streaming platforms LEARN MORE ► Confluent Developer: https://developer.confluent.io CONNECT Subscribe, if you dare: https://www.youtube.com/@ConfluentDeveloper?sub_confirmation=1 Community Slack: https://confluentcommunity.slack.com X: https://x.com/confluentinc Linkedin: https://www.linkedin.com/company/confluent GitHub: https://github.com/confluentinc Site: https://developer.confluent.io ABOUT CONFLUENT DEVELOPER Confluent Developer provides comprehensive resources for developers looking to learn about Apache Kafka®, Apache Flink®, Confluent Cloud, Confluent Platform, and any other technology related to the broader Data Streaming Platform. Content on Confluent Developer includes courses, getting started guides, topical deep-dives, patterns, tutorials, and listings of community events. Learn more at https://developer.confluent.io. #apachekafka #apacheflink #confluent