Unified Data Analytics | Workshop
Unifying Data Pipelines, Business Analytics and Machine Learning with Apache Spark™
Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.
In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your data and ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources. You’ll learn how to use ML frameworks (i.e. Tensorflow, XGBoost, Scikit-Learn, etc.) to train models based on different requirements. And finally, you can learn how to use MLflow to track experiment runs between multiple users within a reproducible environment, and manage the deployment of models to production.
Join this half-day workshop to learn how unified data analytics can bring data science, business analytics, and engineering together to accelerate your data and ML efforts. This free workshop will give you the opportunity to:
- Learn how to build highly scalable and reliable pipelines for analytics
- Deeper insight into Apache Spark and Azure Databricks, including the latest updates with Delta Lake.
- Train a model against data and learn best practices for working with ML frameworks (i.e. - XGBoost, Scikit-Learn, etc.)
- Learn about MLflow to track experiments, share projects and deploy models in the cloud and on-prem
- Network and learn from your ML and Apache Spark peers
AGENDA AT A GLANCE
- 1:30pm-2:00pm Registration & Networking
- 2:00pm-2:15pm Unifying Data Science and Data Engineering
- 2:15pm-2:45pm Data & Analytics with Azure
- 2:45pm-3:15pm Networking break
- 3:15pm-3:45pm Customer Use Case
- 3:45pm-4:30pm Data Engineering Interactive Demo
- 4:30pm-5:15pm Data Science Interactive Demo
- 5:15pm-5:30pm Q&A
Space is limited for this event. Sign up today to reserve your spot!
** Your health and safety is our top priority. As such, we are taking extra precautions in light of the COVID-19 (coronavirus) situation. Specific measures we're taking include staffing the event with local personnel, providing hand sanitizer at registration and disinfecting shared materials regularly.
APJ Senior Sales and Strategy Director, Databricks
Mauricio Toledo joined Databricks as APJ Senior Sales and Strategy Director from Microsoft where he spent 7 years covering EMEA and Asia.
With over 20 years of international experience in Europe, Americas, and Asia, Mauricio has worked for the software, telecommunications, and banking industries. Prior to joining Microsoft, he was the VP of Microsoft Global Alliance at Micro Focus, driving IBM mainframe modernization projects implemented on Microsoft’s technology.
Mauricio received his MBA from the University of Bath in the UK.
APJ Partner Solutions Architect, Databricks
Ben Sadeghi is a Partner Solutions Architect at Databricks, covering Asia Pacific and Japan, focusing on Microsoft and its partner ecosystem. Having spent several years with Microsoft as a Big Data & Advanced Analytics Technology Specialist, he has helped various companies and partners implement cloud-based, data-driven, machine learning solutions on the Azure platform.
Prior to Databricks and Microsoft, Ben was engaged as a data scientist with Hadoop/Spark distributor MapR Technologies (APAC), developed internal and external data products at Wego.com, a travel meta-search site, and worked in the Internet of Things domain at Jawbone, where he implemented analytics and predictive applications for the UP Band physical activity monitor. Before moving to the private sector, Ben contributed to several NASA and JAXA space missions.
Ben is an active member of the open-source Julia language community. He holds an M.Sc. in computational physics, with an astrophysics emphasis.