create a creative ppt for this in 18-19 slides

1. Big Data Overview
• Introduction to Big Data and its significance.

2. What is Big Data?
• Definition: Extremely large datasets that
cannot be handled by traditional applications.

3. Key Characteristics
• High volume, variety of formats, high speed,
variable quality.

4. Why 'Big Data'?
• Data that is too large, fast, or complex for
traditional processing methods.

5. Why is Big Data Growing?
• Explosion of digital data, technological
advancements, business needs.

6. The 4 V's of Big Data
• Volume, Variety, Velocity, Veracity.

7. Big Data Tools & Technologies
• HDFS, NoSQL, Hadoop, Spark, Python, R,
Kafka, Flume.

8. What is Hadoop?
• Open-source framework for distributed
storage and processing.

9. Hadoop Components
• HDFS, MapReduce, YARN.

10. What are Scala and Spark?
• Scala: Concise language for Spark. Spark: Fast,
in-memory data processing.

11. Hadoop vs Spark
• Hadoop: Batch processing, slower. Spark: Real-
time processing, faster.

12. Big Data in Netflix
• Recommends content based on viewing
history.

13. Big Data in Amazon
• Personalized recommendations, demand
forecasting.

14. Big Data in Walmart
• Inventory management, demand predictions.

15. Hadoop in Yahoo & Facebook
• Yahoo: Web data storage. Facebook:
Managing user-generated content.

16. Spark in Uber & eBay
• Uber: Real-time pricing. eBay: Fraud
detection, price optimization.

17. Challenges in Big Data
• Data quality, security, scalability, integration.

18. Future of Big Data
• AI & ML, cloud storage, predictive analytics.

19. Conclusion
• Big Data drives insights, decision-making, and
innovation.