The number of IoT devices that streams data to a connected cloud backend increases daily. This data creates new possibilities for real-time analytics and can fundamentally impact business productivity, especially in industries such as agriculture, healthcare, manufacturing, mining, and many more.
Databricks Unified Data Analytics Platform (UDAP) is the open and unified platform for data analytics and ML workloads On-demand webinar We are pleased to announce the availability of Azure Databricks in the Swiss Azure Datacenters which marks another milestone on the way to digitize Switzerland.
Available on-demand Apache Spark ™️ has become the de facto open source standard for big data processing due to its ease of use and performance. And the open source Delta Lake project enhances Spark’s lead with new capabilities like ACID transactions, Schema Enforcement and Time Travel.
On-demand webinar Data & ML projects bring many new complexities beyond the traditional software development lifecycle. Unlike software projects, after they were successfully delivered and deployed, they cannot be abandoned but must be continuously monitored if model performance still satisfies all requirements.
Best Practices: Data Lakehouse – Herausforderungen klassischer Data Lakes gelöst Webinar September 22, 2020 | 3:00 PM CEST Webinar In diesem Webinar wollen wir Sie über den Erfahrungsstand mit klassichen Data Lakes informieren und mit dem Konzept des “Data Lakehouses” vertraut machen - einer neuen Art analytischer Plattform, in der alle Arten von Daten und Datennutzern zusammenkommen können, um schneller zu Wertschöpfung zu gelangen.
As one of the key tenets of any successful data governance practice, data governance and security is likely to be top of mind for companies seeking to open access their access data in order to drive the use cases of the future as part of your data-driven transformation.
Join us on 8 July for an introductory tutorial on how Databricks can help you manage your end-to-end Machine learning lifecycle. ML development brings many new complexities beyond the traditional software development lifecycle.
Available on-demand In this webinar, Yan Moiseev, Solutions Architect at Databricks will share machine learning best practices learned from working with Databricks customers on ML use cases across various industries. The talk will cover how to set up machine learning initiatives for success, how to address common challenges, and share customer success stories along the way.
As part of our online learning series, our session on 24 June will walk through an introduction of Databricks Ingest - an easy and efficient way of bringing all your data together from different sources into Delta Lake.
The Databricks Online Learning Series aims to provide data team members with the essentials to understand how unified data analytics can bring data science and engineering together to accelerate your ML efforts.
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.
The big data revolution has made it necessary for business leaders to invest in technologies that enable big data analytics. Only decision makers with the best and most informed understanding of their data can set the standard for their business’s success.