Data & Analytics

BigData & Hadoop Admin

Where Big Data developers write jobs, Big Data admins keep the whole cluster alive. This course covers installing and configuring Hadoop, managing HDFS storage and YARN resources, monitoring cluster health, and troubleshooting the issues that come with data at scale. It's aimed at those who want the operations side of the data world.

Duration: 2 mths
Format: Live 1-on-1
Level: Professional
Certificate: Osian

Overview

What this course is about

BigData and Hadoop Admin is an operations-focused course for learners who want to keep distributed data platforms healthy. Live 1-on-1 online classes cover Hadoop 3 cluster architecture, HDFS, YARN, configuration files, service management and practical troubleshooting. Your teacher explains what an administrator checks before a job runs, how nodes share responsibility and how logs reveal faults. It suits Linux users, system administrators and data professionals moving from application work into platform operations.

You practise installation planning, worker and master roles, storage management, replication, rack awareness, queues and resource allocation. Security discussions include users, permissions, Kerberos concepts, encryption considerations and audit thinking, while monitoring covers health checks, metrics, log review and capacity signals. High availability, backup planning, rolling maintenance and recovery are introduced with realistic operational decisions. The aim is not memorising commands, but understanding consequences when a service or node behaves unexpectedly.

Troubleshooting scenarios can involve a full disk, missing blocks, an unhealthy DataNode, a stuck YARN application or an incorrect configuration value. You learn to collect evidence, isolate the layer involved and document a safe response. This administrator track differs from Big Data and Hadoop Development, where the centre is MapReduce, Hive and Spark coding. Flexible one-on-one Hadoop classes let experienced professionals bring their own Linux or cluster questions.

By the end

What you’ll be able to do

Map Hadoop services across master and worker roles
Configure HDFS storage and YARN resource management
Apply permissions and explain Kerberos security concepts
Monitor cluster health through logs and metrics
Troubleshoot node, storage and application failures
Document maintenance, backup and recovery decisions

Syllabus

How the course flows

1
Data FoundationsWeek 1
Data types, spreadsheets and thinking analytically.
2
Querying & WranglingWeek 2
Pulling and cleaning data with SQL and tools.
3
VisualisationWeek 3
Dashboards in Power BI / Tableau that tell a story.
4
Statistics & InsightWeek 4
Core statistics and drawing sound conclusions.
5
Analytics ProjectWeeks 5–8
An end-to-end analysis on a real dataset.

Toolkit

Tools you’ll use

Excel
SQL
Power BI
Tableau
Python (pandas)

Audience

Who this course is for

Linux system administrators entering big data operations
Hadoop support engineers strengthening platform skills
Data engineers who need cluster administration knowledge
Cloud and infrastructure learners studying distributed systems
Working IT professionals responsible for internal data platforms

Where it leads

Roles this opens up

Hadoop Administrator
Maintain HDFS and YARN services while responding to platform health issues.
Big Data Operations Associate
Monitor distributed workloads, review logs and escalate failures with useful evidence.
Data Platform Support Engineer
Assist with configuration, access, capacity and maintenance tasks for analytics systems.

Questions

Before you enrol

Comfort with files, permissions, processes and shell commands is strongly helpful because administration work is operational. The teacher can revise essential Linux commands while keeping the focus on Hadoop services.

This track concentrates on cluster architecture, service configuration, security, monitoring, capacity and recovery. Development training instead spends more time writing MapReduce, Hive or Spark processing logic.

Yes, you examine storage blocks, replication behaviour, worker health and common disk or node symptoms. Exercises focus on gathering evidence before changing a live-style configuration.

The course introduces identities, permissions, Kerberos concepts, encryption considerations and audit needs at an administrator-friendly level. Detailed enterprise deployment decisions are explained as topics that require environment-specific review.

A local or managed lab can demonstrate service roles and troubleshooting, subject to your computer and available environment. The teacher makes clear where a small lab differs from a production cluster.

Scenarios include unhealthy DataNodes, missing blocks, full disks, stuck YARN applications and configuration mistakes. You practise a repeatable sequence of checking logs, isolating the layer and recording the response.