Join Us

AWS Dev Day

June 10, 2020
AWS Santa Monica Office

1620 26th Street

Suite 4000N

Santa Monica, CA 90404

Join MemSQL at Our Santa Monica Dev Day

In this workshop, students will begin by deploying a highly scalable, cloud-native, highly performant MemSQL relational database cluster on AWS. They will then implement an example Internet of Things (IoT) use case and run real-time analytical queries against it with MemSQL.


We will then demonstrate for students how to operationalize a Sagemaker machine learning (ML) model using transforms, part of MemSQL’s Pipelines capability. We will conclude the session by demonstrating how to build an operational dashboard using Sisense powered by the Sagemaker ML model, within the same AWS environment.


Who Should Attend

  • Level of Technical Expertise - 300
  • Data Engineers, Architects, and Developers
  • Database Administrators and Operators
  • Hands on Business Users wanting to learn more about how to accelerate data insights time to value.

Please bring your laptop to participate in this workshop and make sure you have an active AWS account.


Workshop Agenda


Introduction and Setup

Introduction and Setup

Introductions and Workshop Overview; MemSQL and AWS - Creating a Real-Time Database Architecture; Application and Analytic Architectural Patterns leveraging
8:00am - 9:00am

Hands on Workshop: RT Streaming Analytics with Sagemaker and MemSQL

Hands on Workshop: RT Streaming Analytics with Sagemaker and MemSQL

Seamless Deployment of MemSQL on AWS; Implementing an IoT usage case on MemSQL ; How to operationalize a Sagemaker ML model using MemSQL on the AWS Cloud ; How to leverage Sisense's elastic data engine to define a semantic layer and analytical model; How to build advanced and customizable self-serve dashboards and applications on Sisense; Q & A
9:00am - 12:00pm

Location

AWS Santa Monica Office

1620 26th Street Suite

4000N

Santa Monica, CA 90404

About MemSQL

MemSQL is the No-Limits DatabaseTM for Modern Applications. Run both transactional and analytical workloads at scale with an integrated, familiar, durable SQL database
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