
Explore geospatial data processing at scale using LocationTech projects. Learn about challenges, solutions, and integration with Apache frameworks for analyzing large-scale location-based information.

Explore Observables: next-gen async abstraction. Learn high-level concepts, tackle typeaheads, and dive into stream processing for machine learning. Gain confidence in harnessing Observables to simplify asynchronous programming.

Explore data challenges in microservices, using Domain Driven Design to manage complexity. Learn about transactional boundaries, CAP theorem, and technologies like Kafka and Camel for building scalable, autonomous systems.

Explore diverse data distribution strategies for microservices, including CQRS, event sourcing, and reactive programming. Learn to choose optimal approaches for different scenarios and requirements.

Explore serverless datastream processing for real-time data handling, covering message handling, processing, storage, querying, and machine learning using Google Cloud Platform components.

Explore the power of Java's Collector API for efficient data processing. Learn about ready-to-use collectors, create custom ones, and build complex pipelines for enhanced code readability and performance.

Explore processing petabytes of data using Pivotal Cloud Foundry, Google Genomics, and Google Cloud Platform. Learn about microservices, service brokers, and cloud-scale data management for reliable and resilient solutions.

Explore real-time data streaming and analysis in Formula 1 racing using Apache Kafka, Spark, and Drill. Learn how to capture, process, and visualize high-volume automotive data for performance insights.

Aprenda a realizar testes de usabilidade DIY para melhorar a experiência do usuário em aplicativos e sites, usando técnicas acessíveis e eficazes inspiradas no estilo MacGyver.

Learn to enhance app UX using a unified model for batch and stream processing. Explore Dataflow's capabilities through a real-time demo, gaining practical insights on managing and visualizing data streams.

Discover how Hibernate ORM and Elasticsearch can be seamlessly integrated for efficient data synchronization, automatic indexing, and powerful querying capabilities in Java applications.

Learn to create beautiful, interactive data visualizations using D3.js v4. Explore key concepts, APIs, and advanced features like animations, diagrams, and geo/gis for minimal-code, impactful web-based visualizations.

Discover advanced Hibernate features like full-text search, geospatial queries, change auditing, NoSQL persistence, and caching. Learn about new capabilities in Hibernate ORM 5 to enhance your Java applications.

Comprehensive overview of popular stream processing systems for real-time Big Data analytics, comparing Storm, Samza, Spark, and Flink. Explores use cases, architectures, and trade-offs for low-latency data processing.

Explore DeepLearning4J on Apache Spark for IoT anomaly detection using LSTM autoencoder neural networks. Learn scalable machine learning techniques for real-time cognitive IoT applications.

Learn to create impactful data visualizations using R and RStudio. Explore R's capabilities for transforming data into actionable insights through hands-on demonstrations and expert guidance.

Explore real-time data streaming technologies like WebSockets and Server-Sent Events. Learn to transform static APIs into dynamic streams, optimize data transfer, and apply streaming to innovative use cases like drone control.

Explore key-value, document, columnar, and graph data models in NoSQL databases, understanding their differences and ideal use cases for modern data management.

Discover advanced Hibernate features for full-text search, geospatial queries, auditing, NoSQL persistence, and caching. Learn about Hibernate ORM 5 updates and explore the broader Hibernate ecosystem.

Discover how to leverage cloud computing for efficient big data exploration using Google BigQuery, with practical examples from news, Wikipedia, and weather datasets.

Explore property graphs, Apache TinkerPop, and Gremlin query language to extract and discover relationships in connected data. Compare Gremlin queries with SQL and functional code equivalents.