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TiVo: How to Scale New Products with a Data Lake on AWS and Qubole

Big data technologies can be both complex and involve time consuming manual processes. Organizations that intelligently automate big data operations lower their costs, make their teams more productive, scale more efficiently, and reduce the risk of failure.

In our webinar, representatives from TiVo, creator of a digital recording platform for television content, will explain how they implemented a new big data and analytics platform that dynamically scales in response to changing demand. You’ll learn how the solution enables TiVo to easily orchestrate big data clusters using Amazon Elastic Cloud Compute (Amazon EC2) and Amazon EC2 Spot instances that read data from a data lake on Amazon Simple Storage Service (Amazon S3) and how this reduces the development cost and effort needed to support its network and advertiser users. TiVo will share lessons learned and best practices for quickly and affordably ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households.

Join our webinar to learn:
  • How to dramatically reduce management complexities for big data analytics operations on AWS.
  • Best practices for optimizing data lakes for self-service analytics that enable teams to productionize data science and accelerate data pipelines.
  • About using Qubole’s auto-scaling to reduce the complexity and deployment time of big data projects.
  • How to reduce the cost of big data workloads with Qubole’s automated Spot Instance Bidding and management.
When: Available On Demand (please register to view)

Who Should Attend:
Data Engineers, ETL Engineers, Data Scientists, and Managers of Analytics or Data Operation teams who are interested in improving analytics-related process and enabling self-service analytics should attend this webinar. This webinar covers real-world examples for teams who want to maximize workload performance, have quicker access to data for experimentation, focus on optimizing production workloads, and improve big data operations for large scale memory or concurrent workloads.

AWS Speaker: Paul Sears, Solutions Architect
Qubole Speaker: Harsh Jetly, Solutions Architect
Customer Speaker: Ashish Mrig, Sr. Manager, Big Data Analytics, TiVo