Day 2 | HALL 2 - Practical Insights and Best Practices

In today’s data-driven world, ensuring resilience in data architectures is crucial for maintaining seamless operations, minimizing downtime, and enabling real-time decision-making. This session explores the key principles of designing fault-tolerant, scalable, and adaptive data ecosystems that can withstand failures and disruptions.

Key focus areas include strategies for high availability, redundancy, disaster recovery planning, and leveraging distributed computing and cloud-native technologies to enhance resilience. Real-world insights will showcase how resilient data architectures can optimize performance, improve reliability, and support business continuity in an evolving technological landscape

Real-time data pipelines enable organizations to ingest, process, and act on streaming data with minimal latency, ensuring they can make informed decisions instantly.
This session will explore the core components of real-time data pipelines, including event-driven architectures, stream processing frameworks, and scalable data ingestion technologies. We’ll discuss real-world applications such as fraud detection, predictive analytics, IoT monitoring, and personalized customer experiences.
By the end of the session, attendees will gain a deeper understanding of how real-time data pipelines drive agility, enhance operational efficiency, and unlock new business opportunities. Whether you’re a data engineer, architect, or business leader, this talk will equip you with the knowledge to harness the power of real-time data for smarter decision-making.

As organizations increasingly rely on complex data ecosystems, maintaining data quality and trust has become paramount to business success. This discussion explores the critical components and best practices for implementing robust data quality frameworks within modern data architectures. We examine how organizations can establish automated testing, monitoring, and governance processes to ensure data reliability across the entire pipeline – from ingestion to consumption. Special attention is given to emerging tools and methodologies that enable continuous data quality assessment while scaling with growing data volumes and complexity.

In the competitive OTT landscape, delivering an exceptional video Quality of Experience (QoE) is crucial for user satisfaction and retention. This session will explore how data-driven approaches can transform the way QoE is monitored, analyzed, and optimized.
The talk will delve into the key metrics that define QoE, including startup time, buffering frequency, bitrate quality, and playback interruptions. By leveraging real-time analytics, machine learning, and predictive modeling, OTT platforms can proactively identify and resolve issues before they impact the user experience.

Attendees will gain actionable insights into:

Designing scalable data pipelines for QoE monitoring.
Using predictive analytics to anticipate and mitigate streaming disruptions.
Optimizing encoding and delivery processes to reduce latency and improve video quality.

This session is ideal for data engineers, OTT platform architects, and video delivery professionals looking to elevate their platform’s user experience through the power of data.