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Karan Alang, a seasoned expert in big data and AI, shares his extensive journey through technology. With over 24 years of experience, he emphasizes the evolution of data processing from megabytes to petabytes, highlighting the importance of distributed technologies. His insights reveal a deep understanding of how big data and AI can transform industries through innovative solutions.
Alang discusses the significance of selecting the right tools for specific data challenges, advocating for a systematic approach. He illustrates this with examples of using Apache Kafka and Spark for real-time data processing, while Hadoop serves well for batch processing. His perspective on the future of AI emphasizes the need for explainability and ethical considerations, alongside the democratization of AI tools for businesses of all sizes.
• Karan Alang emphasizes the evolution of data processing technologies.
• The future of AI focuses on explainability and ethical considerations.
Machine learning is a subset of AI that enables systems to learn from data and improve over time.
Anomaly detection identifies unusual patterns in data, crucial for real-time insights in network environments.
Explainable AI ensures that AI models provide understandable insights into their predictions and decisions.
Apache provides open-source software frameworks like Hadoop and Kafka, essential for big data processing.
Google Cloud Platform offers scalable cloud solutions that support big data and AI applications.
Amazon Web Services provides cloud computing services that facilitate big data analytics and machine learning.
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