Course Details
Big Data Bootcamp: Accelerated Edition
Big Data
Created On
September 16, 2023Description
Big Data refers to massive and complex datasets that surpass the capacity of traditional data processing methods. It involves vast volumes of data generated at high speeds and encompassing various types. Big data analytics uses specialized tools and technologies to extract valuable insights and drive informed decision-making in diverse industries.
Overview
The Big Data and Analytics Masterclass is an in-depth six-month course designed to provide learners with comprehensive knowledge and practical skills in the field of big data and analytics. **This course is tailored for individuals who want to become proficient in managing, analyzing, and deriving valuable insights from large datasets without a focus on Python programming**. With a focus on various big data technologies and tools, this program equips **participants with the expertise to excel in data-driven decision-making roles**.
Features
- Comprehensive curriculum covering a wide range of big data technologies and tools.
- No prior experience with Python is necessary
- Expert instructors with real-world industry experience.
- Every week doubt clearing session.
- Assignment & Quiz in every module
- Live project with real-time implementation
- Career guidance & Interview Preparation
- Hands-on projects and exercises to reinforce learning.
- Access to cloud-based platforms for practical exercises.
- Industry real-time projects
- Doubt clearing through mail and chat support team
- Resume building
- Internal Hiring
- A supportive learning community
- Certification upon successful completion.
What you'll learn
- Foundations of Big Data:
- Linux Proficiency
- Advanced SQL Mastery
- Hadoop Ecosystem
- NoSQL Database Management
- Data Streaming with Kafka
- Cloud-Integrated Big Data Solutions
- Data Modeling
- Performance Optimization
Prerequisites
Curriculum
- 9 modules
Overview: Understanding the fundamentals of big data, its challenges, and solutions.
Topics Covered:
What is Big Data?
The 5 Vs of Big Data (Volume, Velocity, Variety, Veracity, Value)
Exploding Data Problem: Causes and Implications
Overview: Mastering Linux essentials, commands, and system administration.
Topics Covered:
Linux Fundamentals
Introduction to Linux
Linux Commands and File System
Users, Permissions, and Security
Shell Scripting for Automation
Networking and System Administration
Overview: Comprehensive coverage of SQL for data querying and manipulation.
Topics Covered:
Basic SQL: Introduction, Queries, Aggregate Functions, DDL, DML, DCL
Intermediate SQL: Data Manipulation, Transactions, Joins, Subqueries, Pivoting Data
Advanced SQL: Common Table Expressions (CTEs), Window Functions, Stored Procedures, Database Design Principles
Overview: Understanding Hadoop, its architecture, and Hadoop Distributed File System (HDFS).
Topics Covered:
Hadoop Fundamentals: Introduction, Ecosystem Components
HDFS: Design, Features, Commands
Hive: Introduction, Data Modeling, Optimization Techniques
Overview: Exploring HBase, a NoSQL database, and its advanced concepts.
Topics Covered:
Introduction to HBase: Architecture, CRUD Operations, Filters
Advanced HBase: Performance Tuning, Data Versioning, Replication, Backup, Recovery, Security
Overview: Understanding MongoDB, a NoSQL database, and its advanced capabilities.
Topics Covered:
MongoDB Basics: CRUD Operations, Indexes, Aggregation Framework, Data Modeling
Advanced MongoDB: Data Management, Replication, Sharding, Security
Overview: Delving into Cassandra, a NoSQL database, and mastering its advanced features.
Topics Covered:
Introduction to Cassandra DB: Architecture, Data Modeling, CQL
Data Modeling in Cassandra: Data Types, Keyspaces, Clustering, Denormalization, Indexes
Advanced Cassandra DB Concepts: Consistency Levels, Data Replication, Security, Performance Tuning
Overview: Understanding Kafka and its role in data streaming and integration.
Topics Covered:
Introduction to Kafka: Architecture, Topics, Brokers, Producers, Consumers
Kafka Producer and Consumer APIs: Message Batching, Partitioning
Kafka Stream Processing: Streams API, Windowing, Aggregations, Kafka Connect
Overview: Applying your knowledge to real-world projects in big data and analytics.
Sample Projects:
ETL Data Pipeline on AWS EMR Cluster
Modern ETL Data Pipeline using Informatica Cloud
Data Pipeline based on Messaging using Airflow
Hive Project for E-commerce Data Warehousing
Financial Complaint Analysis
AWS Glue Data Pipeline
Instructors
Skoliko Faculty
- 9 Modules
- 45 Hours
- Big Data
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