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Cloud native data lake and data processing

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Cloud native data lake and data processing

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Happy to announce yet another interesting IBM Cloud developers in Stuttgart Meetup session. This time, we talk about data processing and data lake as achieved Cloud Natively.

I am happy to announce our guest speaker Dr Gil Vernik, Cloud and Big Data Senior Researcher and Technical lead from IBM Haifa Research Lab and Torsten Steinbach, STSM Cloud Data & Analytics, IBM Boeblingen Lab.

Agenda

18:00 Get together, Snacks & Drinks
18:30 "Serverless computing for data scientists and industry – your small step for a big difference" - Dr. Gil Vernik, IBM Haifa
19:30 Break
19:45 "A complete serverless data analytics solution stack" - Torsten Steinbach, IBM Boeblingen
20:30 Networking

"Serverless computing for data scientists and industry – your small step for a big difference"

Monte-Carlo simulations, HPC flows, data pre-processing or Big Data analytics - all share similar challenges, where and how to scale the computations, what is the setup overhead and does scaling require modifying business logic of the computation. Dr Vernik will talk about how to leverage serverless computing in the cloud to meet this challenge.
He would show the open source PyWren-IBM framework developed as part of CloudButton Horizon 2020 project, that introduces serverless computing with minimal effort and its new fusion with serverless computing brings automated scalability and the use of existing frameworks into the picture.

"A complete serverless data analytics solution stack"

Can you also manage data and do relational processing with SQL in a serverless form factor? Yes, you can. With serverless SQL services you do not provision any system resources. All what you provide is your SQL statement that references data stored in one or more repositories in the cloud, such as object storage, NoSQL databases or also Db2. You can also choose a repository where the results of the SQL should be written in order to conduct serverless ETL. Torsten will explain the serverless data analytics solution stack, consisting on serverless storage, serverless application runtimes and serverless SQL analytics and how they work together to run entire solutions in a serverless fashion.

Join us for a deep dive session!!

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