Big Data Guide 🚀📊

1. What is Big Data?

Big Data refers to extremely large datasets that cannot be processed using traditional tools like Excel or basic Python.

2. 5 Vs of Big Data

Volume → Huge size
Velocity → High speed
Variety → Different types
Veracity → Data quality
Value → Useful insights

3. Tools

- Hadoop
- Spark
- Hive
- Kafka

4. Hadoop

Distributed storage (HDFS)
Processes large data in clusters

5. Apache Spark

Fast processing engine
Supports Python (PySpark)

6. PySpark Example

from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("Test").getOrCreate()

df = spark.read.csv("data.csv", header=True)
df.show()

7. Data Pipeline

Data → Storage → Processing → Analysis → Visualization

8. Real Use Cases

• Social media data 📱
• Banking systems 💰
• E-commerce analytics 🛒
• Streaming data (real-time) 🎥