Part 7/10:

• Proactive monitoring: AI can continuously track volume, latency, and error rates, providing alerts and suggestions for remedial actions.

Practical Business Applications

Beyond technical efficiency, Mangjunad emphasized the potential for AI-driven pipelines to solve real business problems, such as:

• Demand forecasting: Using smart pipelines to analyze transaction data for stock level predictions.

• Operational efficiency: Early detection of data volume surges or latency issues to avoid bottlenecks.

• Stock and inventory management: Minimizing stockouts through predictive analytics integrated with data pipelines.