FUNDAMENTALS OF BIG DATA & REAL-TIME ANALYTICS
Harness the Power of Big Data for Instant Insights and Smarter Decisions
Course Schedule
| Venue (InHouse) | Fees |
|---|---|
| At Your Organization Premises | Ask For The Quotation |
Course Introduction
This course introduces participants to the core concepts, technologies, and tools used in Big Data and Real-Time Analytics. It equips professionals with the foundational knowledge required to understand the data lifecycle, analytics pipelines, and how organizations can gain instant business intelligence from fast-moving data streams. You will explore architectures such as Hadoop and Spark, and learn how real-time systems like Kafka and Flink process and deliver insights on the go.
Course Objectives
By the end of the course, participants will be able to:
- Understand the fundamentals of Big Data, its ecosystem, and challenges
- Explore real-time data processing concepts and streaming analytics
- Familiarize with key Big Data and streaming tools (Hadoop, Spark, Kafka, etc.)
- Understand how real-time insights can support critical decision-making
- Learn about data governance, quality, and security in Big Data environments
Key Benefits of Attending
Organizations need to move beyond traditional BI to data-driven real-time decision-making. This course will prepare you to be part of digital transformation initiatives and to support scalable, fast, and intelligent data-driven operations.
Intended Audience
- Data Analysts and Data Scientists
- IT Professionals and Software Engineers
- Business Intelligence Professionals
- Project Managers and Digital Transformation Leaders
- Anyone interested in Big Data and streaming analytics fundamentals
Individual Benefits
- Gain practical insights into modern data processing ecosystems
- Develop skills for roles in data engineering and real-time analytics
- Understand architectural choices and best practices for Big Data systems
Organization Benefits
- Build internal Big Data literacy and capability
- Enable faster, data-driven decision-making
- Streamline operations using analytics pipelines and automation
Instructional Methdology
- Instructor-led presentations and interactive lectures
- Live demos and tool overviews
- Group discussions and architecture walkthroughs
- Hands-on exercises using simulated data environments
Course Outline
DETAILED 5-DAY COURSE OUTLINE (Customizable)
Training Hours: 07:30 AM – 03:30 PM
Daily Format: 3–4 Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Big Data Foundations
- 07:30 – 09:30 – Module 1: Introduction to Big Data – 5 V’s and Market Trends
- 09:45 – 11:15 – Module 2: Big Data Architecture Overview – Batch vs Stream
- 11:30 – 01:00 – Module 3: The Hadoop Ecosystem – HDFS, MapReduce, Hive
Day 2: Real-Time Analytics Essentials
- 07:30 – 09:30 – Module 4: Real-Time vs Batch Analytics – Key Differences
- 09:45 – 11:15 – Module 5: Streaming Concepts – Windows, Latency, Throughput
- 11:30 – 01:00 – Module 6: Kafka Basics – Topics, Producers, Consumers
Day 3: Tools & Technologies
- 07:30 – 09:30 – Module 7: Apache Spark – Spark Core, SQL, Streaming
- 09:45 – 11:15 – Module 8: Real-Time Data Pipelines – Kafka + Spark Integration
- 11:30 – 01:00 – Module 9: NoSQL Databases for Big Data (MongoDB, Cassandra)
Day 4: Use Cases and Implementation
- 07:30 – 09:30 – Module 10: Real-World Applications (IoT, Finance, Retail, Telco)
- 09:45 – 11:15 – Module 11: Designing Scalable Streaming Pipelines
- 11:30 – 01:00 – Module 12: Data Governance, Security & Quality Controls
Day 5: Strategy and Hands-On Lab
- 07:30 – 09:30 – Module 13: Building Your First Real-Time Analytics Flow
- 09:45 – 11:15 – Module 14: Dashboards and Alerts with Open-Source Tools
- 11:30 – 01:00 – Module 15: Final Project Presentation, Group Discussion & Certification
Certification
All participants will receive a Certificate of Completion for Fundamentals of Big Data & Real-Time Analytics, acknowledging their understanding of critical data systems and real-time processing techniques.