Machine Learning/Serverless Analytics And SAP In The Cloud

button-icon-arrow-right
button-icon-arrow-left

button-icon-arrow-leftBack

Event

Machine Learning/Serverless Analytics and SAP in the Cloud

9 April 2019

Cambridge

Added 28-Mar-2019

In this meeting we have two great presentations for you! First up is Jeff Forrest of BP whom will be giving us a high-level overview of some of the decisions that need to be taken into account when considering the AWS Cloud. Jeff will describe these decisions in-light of a large scale SAP migration that was performed recently within BP. Secondly, we have AWS Evangelist and regular visitor Danilo Poccia whom will showing us (with demos!) how you can use Machine Learning to conduct Serverless Analytics in order to extract insights and actionable information in a cost-effective manner.

We are hosted, as ever, by our dear friends from Metail.

We look forward to welcoming you!

18:30: Arrival

19:00: Announcements - Jon Green (Adeptium)

19:10: PRESENTATION: “BP SAP in the Cloud - Overview of BPs SAP Journey in AWS and the Benefits Achieved” – Jeff Forrest (BP)

In this talk Jeff will be describing some of the decisions taken when BP recently undertook a large-scale SAP migration to AWS. Jeff will describe the reason BP took the decision to move their SAP estate to AWS, along with some of the architectural considerations made along the way.

This talk is perfect for those considering a journey into AWS as it covers some of the basic questions that need to be asked

20:10: Break

20:20 : PRESENTATION/DEMO: "Using Machine Learning for Serverless Analytics" - Danilo Poccia (AWS)

Extracting insights and actionable information from data requires a broad array of technology that can work with data in an efficient, scalable, and cost-effective way. AWS offers a comprehensive set of services to handle every step of the analytics process chain, without having to think about servers and the underlying infrastructure. In this session, we’ll implement step-by-step a serverless analytics platform that can process static content (such as files) or real-time data (such as video, audio, application logs, website clickstreams, and IoT telemetry), enrich data using API-driven machine learning services, query data instantly, and build visualizations to perform ad-hoc analysis.

21:20 Social, Pizza, Networking, Close.

Top