Big data training

12 Modules

A. Big Data Administration

Module 1: Introduction to Big Data

Understanding the fundamentals of Big Data
Overview of Big Data ecosystems and technologies

Module 2: Big Data Infrastructure Setup

Installation and configuration of Hadoop, Spark, and related components
Cluster management and optimization

Module 3: Hadoop Administration

Managing Hadoop Distributed File System (HDFS)
Job scheduling and resource management with YARN

Module 4: Apache Spark Administration

Setting up and managing Spark clusters
Monitoring and optimizing Spark applications

Module 5: Security and Data Governance

Implementing security measures in Big Data environments
Data governance and compliance best practices

Module 6: Backup and Recovery

Developing strategies for data backup and recovery
Handling fault tolerance in Big Data systems

B. Data Engineering

Module 1: Introduction to Data Engineering

Overview of data engineering concepts and principles
Role of data engineering in the Big Data landscape

Module 2: Data Ingestion and Processing

Techniques for ingesting data into Big Data platforms
Batch and real-time data processing using Apache Spark

Module 3: Data Warehousing and ETL

Designing and implementing data warehouses
Extract, Transform, Load (ETL) processes and best practices

Module 4: Data Modeling and Optimization

Understanding data models for Big Data
Optimization strategies for efficient data processing

Module 5: Data Quality and Governance

Ensuring data quality in Big Data environments
Implementing data governance frameworks

Module 6: Capstone Project

Real-world data engineering project to apply acquired skills

We align with your company process standards, while recommending best practices from ITIL and PMP project flow cycles.

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