
IT mavens like Google, Amazon and IBM as well as growing start-ups are always in search of Big Data experts. So we have come up with a tutorial on Apache Hadoop to help you get started on your Data Analytics path!

Learn Big Data fundamentals, Hadoop setup, Linux basics, scaling concepts, and HDFS architecture in this comprehensive tutorial series for beginners and professionals.

Learn Hadoop administration with Cloudera, covering installation, configuration, security, high availability, and performance tuning for enterprise-level data management and analytics.

Learn Big Data and Hadoop essentials, including HDFS, MapReduce, YARN, Hive, and HBase. Explore career paths, architecture, and practical problem-solving in Hadoop ecosystems.

Comprehensive introduction to Big Data technologies, covering HDFS, MapReduce, Hive, Pig, Spark, NoSQL, HBase, Sqoop, Flume, and Kafka. Ideal for beginners seeking a solid foundation in Hadoop ecosystem.

Simplified approach to Hadoop ecosystem: architecture, HDFS, MapReduce, YARN, security, and practical examples. Includes Google Cloud integration for hands-on experience.

Comprehensive hands-on introduction to data engineering, covering data lake architecture, Cloudera tools, Apache Sqoop, and practical HDFS and MySQL operations.

Explore Xiaomi's HDFS data governance practices, focusing on hot and cold data tiered storage solutions. Learn about cold data analysis, S3 integration, and future plans for optimizing data management.

Explore Pinterest's migration of Apache Spark clusters from HDFS to S3, addressing technical challenges, optimizing performance, and achieving a smooth transition process.

Explore Hadoop and Big Data concepts in this NightHacking presentation, focusing on their integration with Java for efficient data processing and analysis.

Explore advanced Spark and Mesos integration for secure, isolated Big Data environments. Learn to enhance protection, manage secrets, and implement network solutions in enterprise-level deployments.

Learn to build robust streaming data pipelines using Apache Spark, Kafka, and Camel. Explore ETL challenges, data management, and lessons from running these technologies in Docker.

Optimize HDFS Transparent Encryption performance by balancing CPU cores and hardware accelerators. Learn to leverage OpenSSL 3.0 for dynamic resource allocation and improved efficiency in cloud services.

Explore ByteDance's HDFS clustering practices for 100 billion files. Learn about storage scheduling, multi-region computing, and data management techniques for large-scale big data applications.

Explore Azure Blob Storage's capabilities for unified data lakes, multi-protocol support, and secure scaling solutions to effectively manage and store data from various sources in the cloud.

Explore CubeFS, a cloud-native distributed storage solution for big data, machine learning, and data sharing. Learn about its protocols, redundancy strategies, and hybrid-cloud acceleration features.

Learn to reduce recovery times and achieve high availability for distributed applications on DC/OS using external persistent volumes, with practical examples and demonstrations.

Learn to build robust stateful applications using the DC/OS SDK, simplifying development on Apache Mesos and DC/OS platforms while standardizing service interactions and handling common challenges.

Explore strategies for reducing recovery times and achieving high availability in DC/OS using external persistent volumes, focusing on distributed applications like Cassandra and HDFS.

Explore HDFS CSI plugin design for Kubernetes in on-premises big data clusters, including architecture, best practices, and performance analysis using Spark and TPC-DS benchmarks.

Explore VMware architecture, vulnerabilities, and escape techniques. Learn about backdoors, PCI, HDFS, and Host Open exploits. Includes live demo and Metasploit module discussion.