Big Data Overview 1 Day Workshop | Canberra, ACT

• Duration: 1-Day Practical Training (8 Hours)
• Timing: 9:00 AM – 5:00 PM (including breaks)
• Location: Location shared via email ( Complete Address )
• Format: Classroom Training (Virtual option available on request)
• Language: English
• Certificate: Course Completion Certificate
• PDUs Awarded: 8 Professional Development Units
• Contact: [email protected]

Unlock the power of Big Data and explore how it drives innovation and business success across industries.
This 1-Day Big Data Overview Workshop is designed to provide professionals with a clear understanding of Big Data concepts, technologies, tools, and applications.

You’ll discover how organizations collect, process, and analyze massive data sets to uncover valuable insights, improve decision-making, and enhance business performance.

Through real-world examples and case studies, you’ll gain exposure to leading technologies such as Hadoop, MongoDB, and data mining tools that form the backbone of modern data ecosystems.

Whether you are an IT professional, software engineer, data enthusiast, or business analyst, this workshop will equip you with foundational knowledge to start your journey into Big Data Analytics.

✅ Understand the fundamentals, history, and characteristics of Big Data
✅ Learn about key Big Data technologies such as Hadoop, MongoDB, and data warehouses
✅ Explore enterprise, social media, and public data sources for analytics
✅ Gain insight into data mining concepts and tools used to extract business value
✅ Understand Big Data privacy, ethics, and governance
✅ Learn from real-world Big Data success stories and case studies

This workshop is ideal for:

• Software Engineers and Developers
• IT Architects and System Administrators
• Business Analysts and Data Professionals
• Research Analysts and Technical Managers
• Anyone interested in learning how Big Data can transform business operations

Prerequisites: Basic understanding of IT systems, databases, or programming concepts.

9:00 AM – 9:30 AM | Registration & Introduction
Welcome, agenda overview, and participant introductions.

9:30 AM – 10:45 AM | Module 1: Big Data Fundamentals

• Big Data: History, Overview, and Characteristics
• Big Data Architecture and Ecosystem
• Big Data Technologies: Overview of Hadoop, Spark, MongoDB
• Big Data Privacy, Security, and Ethics
• Real-World Big Data Projects and Success Stories

10:45 AM – 11:00 AM | Tea / Coffee Break

11:00 AM – 12:30 PM | Module 2: Big Data Technologies & Tools

• Introduction to Hadoop and HDFS
• Overview of MapReduce and Data Processing
• Introduction to NoSQL Databases (MongoDB, Cassandra)
• Cloud Platforms for Big Data (AWS, Azure, Google Cloud)

12:30 PM – 1:30 PM | Lunch Break

1:30 PM – 3:00 PM | Module 3: Big Data Sources

• Enterprise Data Sources (ERP, CRM, Transactional Systems)
• Social Media Data Sources (Twitter, Facebook, LinkedIn APIs)
• Public Data Sources (Government, Open Data Platforms)
• Data Integration and ETL Concepts

3:00 PM – 3:15 PM | Tea / Coffee Break

3:15 PM – 4:30 PM | Module 4: Data Mining – Concepts and Tools

• Introduction to Data Mining
• Data Mining Techniques (Classification, Clustering, Association)
• Tools Overview: RapidMiner, Weka, KNIME, Orange
• Case Study: Applying Data Mining in Business

4:30 PM – 5:00 PM | Q&A, Wrap-Up, and Certification
Recap of key takeaways, discussion on next steps in Big Data learning, and distribution of participation certificates.

✔ Comprehensive understanding of Big Data concepts and ecosystem
✔ Knowledge of Big Data technologies like Hadoop and MongoDB
✔ Familiarity with data sources and mining tools
✔ Certificate of Participation from Knowledge Que
✔ Networking opportunity with professionals and peers

Offers & Discounts

🎉 Group Discounts Available:

5–10 participants → 10% Discount

11–20 participants → 15% Discount

Corporate & Team Training Available

Want this course delivered at your workplace or for your team? We offer customized onsite and virtual sessions for companies.📩 Email us at [email protected] for details.

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