• What we'll do
As IoT data grows in size, value, and importance - so are the demands of businesses in how they leverage and monetize this information. Piero Cinquegrana, Senior Product Manager, from Qubole will discuss several customer case studies and data science best practices of how companies are solving their IoT big data use cases successfully in the cloud. Piero will cover how companies like Auris Robotics, Samsung SmartThings, Lyft, Tivo, Turner Broadcasting, Under Armour, and Autodesk have made scaled out their big data applications. He will also cover how these companies Data teams (data scientists, data analysts and data engineers) are focusing on the value of their data rather than the infrastructure, and some of the popular technologies that have paved the way here. Piero Cinquegrana is the Data Science Senior Product Manager at Qubole. He is responsible for delivering an end-to-end offering to data scientists using big data in the cloud. Prior to Qubole, Piero was a Senior Data Scientist for over 5 years at Marketshare/Neustar, a leading marketing cloud firm in Los Angeles. In that role, Piero was a key contributor in launching Marketshare's TV app and was instrumental in reducing deployment time of the Strategy app by over 30%. Piero Cinquegrana holds an M.A. in Political Science at UCLA where he acquired his passion for data and statistics.
1 - What is the state of data science today and how are companies starting to advance with data science across the world using Qubole (best practices, key trends, tech to watch)
2 - Examples and lessons learned from data science case-studies with the connected world and IoT
3 - How companies are leverage our Open Source Tuning Tool for optimizing resource utilization with Apache Spark
Qubole is a cloud-based data platform with managed autoscaling for Hadoop, Spark, Presto and other big data tools. Companies are using Qubole today to collaborate from development to production big data workloads and scale out with the technology's unbeatable cloud-optimized agility, flexibility, and cost savings.
About the Spark tuning tool - Qubole recently Open Sourced a Spark tuning tool to profile Spark applications, you can use the tuning tool in your development phase by profiling each fragment of code piece by piece. It works with both Python and Scala to improve application performance. One of the pitfalls of Spark is that it is a beast to configure and wrangle. The massive amount of configurations needed to run different workloads at scale can make it unstable if done improperly. This tool aims to remove the complexities of getting actionable insights out of your live Spark jobs.
• What to bring
• Important to know