Big Data Training Courses

JBI Training offers three courses in this group. Big Data Introduction is a three-day course covering the big data landscape, core concepts, and the Hadoop ecosystem for professionals new to the field. Hadoop Administration is a three-day course for IT professionals responsible for deploying and managing Hadoop clusters. SQL is a two-day course covering structured query language for working with relational databases — a foundational skill for anyone working with data at any scale. All courses are available as scheduled classroom sessions in London, as live online instructor-led training, or as customised onsite programmes for data and IT teams.

Hadoop is an open-source distributed computing framework designed to store and process very large datasets across clusters of commodity hardware. It consists of two core components — HDFS (Hadoop Distributed File System) for distributed storage, and MapReduce for distributed batch processing — along with a broader ecosystem of tools including Hive, Pig, HBase, Sqoop, and Flume. JBI's three-day Big Data Introduction course covers the big data landscape and use cases, the Hadoop architecture and ecosystem, working with HDFS, an introduction to MapReduce, querying data with Hive, and an overview of how Hadoop relates to modern cloud-based big data platforms such as Azure Databricks, AWS EMR, and Google Dataproc. It is suited to data engineers, developers, and IT professionals who are new to big data technologies.

The Hadoop Administration course is a three-day programme for IT professionals and system administrators responsible for deploying, configuring, and managing Hadoop clusters. It covers planning and installing a Hadoop cluster, configuring HDFS and YARN, managing cluster nodes and resources, monitoring cluster health and performance, configuring Hadoop security using Kerberos and ACLs, backup and disaster recovery for Hadoop data, capacity planning and tuning, and troubleshooting common cluster issues. It is suited to system administrators, infrastructure engineers, and DevOps professionals who are responsible for the operational reliability of Hadoop-based data infrastructure.

SQL (Structured Query Language) is the foundational language for querying and manipulating data in relational databases, and it remains one of the most widely used skills across data engineering, analytics, and application development. It is included in this group because SQL skills are directly relevant to big data work — Hive uses a SQL-like syntax for querying data in Hadoop, Spark SQL enables SQL-based queries on large distributed datasets, and modern cloud data warehouses such as Azure Synapse, BigQuery, and Snowflake are all queried primarily using SQL. JBI's two-day SQL course covers database design principles, SELECT queries, filtering and sorting, joins, aggregations, subqueries, and data modification — providing the foundational data querying skills needed across virtually every data platform.

Yes on both counts. While Hadoop remains in active use in many large enterprise and financial services environments, the big data landscape has evolved significantly with the rise of cloud-native platforms such as Azure Databricks, AWS EMR, Google Dataproc, and Apache Spark. JBI's Big Data training content is reviewed to reflect this context, ensuring delegates understand both the Hadoop ecosystem and how it relates to modern cloud-based alternatives. All courses can be delivered as customised onsite or online programmes for corporate data engineering and IT teams, with content tailored to the organisation's specific data infrastructure and platform environment. JBI has delivered big data and data engineering training for organisations including the BBC, NHS, RBS, Sky, EDF, and Cisco.