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Discover Apache Superset's new extensions architecture that enables rapid expansion of BI capabilities while simplifying development and maintenance workflows.
Explore real-time data processing strategies from Uber, Razorpay, and Stripe to unlock speed, scale, and actionable insights for streaming analytics implementation.
Discover ClickHouse fundamentals and advanced techniques for real-world observability workloads, from columnar storage basics to custom inverted indexes and terabyte-scale optimization.
Discover how to build an open source observability stack that tracks every frame of video games, handling thousands of events per 1/60th second when traditional databases fail.
Discover how open-source analytics transform public benefit systems through real-time verification platforms processing 850K+ daily transactions with Apache Kafka, Airflow, and ML tools.
Explore open source database architectures powering financial analytics, handling 65,000+ transactions/second with Apache Cassandra, PostgreSQL, and ClickHouse for trading platforms.
Discover how to build a semantic search app in 300 lines of Python to fix broken FAQ systems, using TiDB and Amazon Bedrock for sub-100ms responses that actually solve support tickets.
Discover how to build and optimize real-time analytics applications using StarRocks, focusing on performance, scalability, and integration with various data sources for user-facing scenarios.
Discover how to create powerful business intelligence dashboards using Apache Superset, an open-source platform that delivers cost-effective and customizable data visualization solutions.
Discover how Grafana evolves beyond monitoring to become a comprehensive data analysis platform, featuring new visualization tools and enhanced transformation capabilities for diverse analytical needs.
Explore real-time data querying using SQL engines like Apache Flink, ksqlDB, Trino, and RisingWave for streaming data analysis on Kafka and other message buses.
Explore how an open standard for semantic layer can unify data tools, enhance analytics, and streamline workflows for better data management and user experiences.
Discover how to build robust AI systems using Hugging Face's open models and Kedro pipelines, moving beyond commercial AI to create customizable and transparent machine learning solutions.
Explore how traditional ETL tools like Singer and Meltano can enhance data pipeline management for LLM applications, addressing production-level challenges beyond basic LangChain capabilities.
Dive into stream processing fundamentals and learn to build real-time data applications using Python's Bytewax framework, debunking common misconceptions along the way.
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