The Open Source Delta Lake Project is now hosted by the Linux Foundation.
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Join us at Spark + AI Summit San Francisco - Register by 1/17 to Save $700.
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The Open Source Delta Lake Project is now hosted by the Linux Foundation.
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Join us to help data teams solve the world's toughest problems
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rstudio::conf, the conference for all things R and RStudio, will take place January 29 and 30, 2020 in San Francisco, California. It will be preceded by Training Days on January 27 and 28.
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. 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.
Modern data lakes leverage cloud elasticity to store virtually unlimited amounts of data "as is", without the need to impose a schema or structure. Structured Query Language (SQL) is a powerful tool to explore your data and discover valuable insights. Delta Lake is an open-source storage layer that brings reliability to data lakes with ACID transactions, scalable metadata handling, and unified streaming and batch data processing. Delta Lake is fully compatible with your existing data lake. Join Databricks and Microsoft as we share how you can easily query your data lake using SQL and Delta Lake on Azure.
Successful data science relies on solid data engineering to furnish reliable data. Delta Lake is an open source storage layer that brings reliability to data lakes allowing you to provide reliable data for data science and analytics. This webinar will cover modern data engineering in the context of the data science lifecycle and how the use of Delta Lake can help enable your data science initiatives.
Join this meetup to learn how Delta Lake can help you build robust production data pipelines at scale. Every enterprise today wants to accelerate innovation by building Data and ML into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of Data and ML frameworks, and moving models in development to production.
Agenda: 6:30 pm Food & Mingle Time 7:00 pm Introduction 7:05 pm Spark Payment Insights by David McKennell & Thomas Mambrini / Wirecard 7:40 pm Break 7:55 pm Distributed Portfolio Risk Management using Spark by Nima Nooshi / Databricks 8:30 pm Cake & Networking 9:00 pm Official End
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts.In this workshop, we'll cover best practices for enterprises to use powerful open source technologies to simplify and scale your 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.
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
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. 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.
Join this hands-on lab to learn how Delta Lake can help you build robust production data pipelines at scale. Every enterprise today wants to accelerate innovation by building Data and ML into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of Data and ML frameworks, and moving models in development to production.
