In this interactive virtual workshop, the Databricks Media and Entertainment Technical Director will walk through the different Databricks solution accelerators we have developed for every stage of the customer journey — from acquisition to engagement, retention and beyond.
On April 21 and 22 2021, more than 2,000 experts and decision-makers will discuss new trends and exciting challenges around #BigData and #AI at the Big-Data.AI-Summit 2021. Meet the Databricks team in the virtual expo area or join the presentation "Data Mesh in Practice: how to set up a data-driven organization" by Zalando on April 21, 4:10-4:30 pm CEST, Hari Seldon Stage
Run by Databricks and Spark experts, this online session is designed to help data engineers, SQL analysts, and BI professionals come away with a deeper understanding of the fundamentals of Databricks’ lakehouse architecture, which combines the best elements of data lakes and data warehouses.
Join us for virtual tech talks at Data + AI Meetup about MLflow Integration from Azure ML and Algorithma sponsored by the Databricks MLflow Team. It will be simultaneously broadcasted live on YouTube and LinkedIn.
In this live workshop, we’ll discuss how to get started with Databricks on Google Cloud to build an open data lake for all your data, analytics and AI. Learn how to build a curated data lake that is reliable, highly scalable and performant for all big data engineering, streaming, data science and machine learning, SQL Analytics, BI and reporting workloads.
Run by Databricks and Spark experts, this online session is designed to help data scientists and machine learning engineers explore their data, build and productionise models, and share their analyses using the Databricks Lakehouse platform. You will get a deeper understanding of the fundamentals of how Databricks’ collaborative environment allows data teams to run all analytics processes in one place, and manage ML models across the full life cycle with MLflow.
The potential of data and AI is extraordinary. But how can practitioners apply it to tangible, real-use cases? Data and AI can address multiple challenges. For example, in digital marketing, personalising the user experience is becoming a critical success factor. Personalisation requires data in large quantities, and in the appropriate format and quality. However, exploiting the available information presents a significant challenge for most companies. Smart Digital utilises Databricks for the automated processing of big data, and as the basis for AI-driven, individualised user experiences in real-time.
Join us for the final session in a four part series with Salesforce Engineering. As we build our Engagement Delta Lake on Databricks Workspace, one of the challenges is how to automate the integration testing of our Spark jobs in the CI/CD pipeline. We came up with two designs to tackle the challenge: Namespace Deployment and Scenario Based Testing. In this talk, we will discuss the rationale and implementations of the two designs.
Join financial services industry leader, Junta Nakai, and Databricks solution architects as they share how institutional investors can leverage the power of data and AI to mitigate risk and gain a competitive advantage. We will also be joined Martin Williams, Head of Reference Data Business Development at ICE, to discuss how ESG data empowers investors to make more informed investment decisions.
Struggling to make your data lake analytics-ready? Join us at the upcoming AWS Summit Online ANZ and hear how Databricks Lakehouse is simplifying the common struggles of data teams by streamlining data processing workflows and making data ready to use for analytics, data science and machine learning.