Day 2 | HALL 2 - Practical Insights and Best Practices

DataOps enables organizations to harness the full potential of their data assets, driving innovation and gaining a competitive edge in the market.is crucial in today’s data-driven world. One of the key aspects of DataOps is its focus on collaboration and automation across different teams involved in managing data. By fostering collaboration between data engineers, data scientists, and operations teams, DataOps ensures that everyone is aligned towards the common goal of delivering high-quality data products. Automation streamlines processes such as data ingestion, transformation, and deployment, reducing manual errors and improving overall efficiency.

Moreover, DataOps emphasizes continuous integration and delivery practices, enabling organizations to adapt quickly to changing data requirements and business needs. This agility is essential in today’s fast-paced business environment, where the ability to respond rapidly to market changes can make the difference between success and failure.

The evolution of data engineering encompasses transformative concepts driving advancements in knowledge graphs, data discovery, synthetic data generation, text-to-SQL transformations, data quality management and generative AI datasets.
Knowledge graphs facilitate semantic data modelling and interconnected data querying. Data discovery empowers insights extraction through metadata analysis and automated profiling. Synthetic data generation mitigates data scarcity using generative AI for realistic datasets. Text-to-SQL bridges natural language queries with structured databases, enhancing accessibility. Data quality management ensures integrity, consistency, and reliability through profiling and error remediation. Generative AI datasets fuel innovation and creativity in generative models. This talk will take the audience through real-world cases of the above-mentioned concepts.

MaaS, or Metrics as a Service, is a cloud-based model that provides organisations access to many metrics and analytics capabilities without building and maintaining complex data pipelines or infrastructure. In a MaaS platform, users can define, compute, visualise, and manage metrics and key performance indicators (KPIs) using a centralised and scalable solution.

Booking Holding is the world’s leading provider of online travel and related services and operates through 5 primary consumer facing brands : Booking,com, Priceline, Agoda, Kayak and Opentable, as well as through a network of subsidiary brands. The next phase of growth at booking will be driven by providing a unified connected trip experience and modernisation which will make it easier for everyone to experience the world. As part of this talk Ankur and Sucharita will highlight how booking is modernizing the data platform to Provide a modern, governed, self service Data and ML platform – facilitating data driven decision making and be future ready to support experimentation and AI/ML use cases while supporting the large booking business.

Data observability has garnered considerable interest in recent times. It has evolved from Observability, which relied on monitoring, logging, tracing, etc. However, the expectations associated with data observability and its key tenets have shifted significantly from traditional ways of thinking and implementing it. This session will delve into more practical aspects of Data Observability and how individuals, organisations, and platforms should think differently to gain maximum value from it in a cost-efficient manner.