The Fortune 1000 are planning to increase their AI and Machine Learning investments in 2022 and beyond across all industries and sectors. Rapid AI advances are enabling supply chain efficiency, capital markets agility, energy resilience, marketing performance, reshaping the pharmaceutical value chain, and triggering advances in medical treatments. AI predictive analytics and decision-making support will transform entire industries and generate...

Data sharing is crucial to drive business value in today’s digital economy. Organizations are looking to securely share data with their partners/vendors, internal line of business, and generate revenue streams with data monetization. Databricks Delta Sharing empowers organizations to seamlessly and securely share and consume live data without the limitations enforced by vendor-specific sharing networks or constraints of legacy delivery s...

Confluent, AWS, Databricks, and MongoDB are coming to New York. Today’s customers expect real-time data from businesses. To rise to these expectations, modern organizations are deploying data streaming technology, the most popular of which is Apache Kafka. Join us to talk through what “a day in the life” of data professionals who work with Kafka looks like now, and what Confluent’s cloud-native, Kafka-based platform can...

Organizations must embrace the cloud to harness all their data and leverage AI. But many still have their data trapped in on-premises data lakes and data warehouses — in environments like Hadoop. Join us to learn how enterprises are unleashing the power of highly scalable big data with cloud-based alternatives like the Databricks Lakehouse Platform — a simple, open and collaborative platform for all your data, analytics and AI need...

Geospatial analytics has evolved beyond analyzing static maps. Today, enterprises have access to diverse geospatial data like high-res images, streaming video, and GPS data. By applying advanced analytics to these geospatial datasets, organizations can deliver on a broad range of use cases across all industries. Unfortunately, most organizations lack the proper data architecture to prepare these large, complex datasets for downstream analytics...

As organizations continue to develop their machine learning (ML) practice, there’s a growing need for robust and reliable platforms capable of handling the entire ML lifecycle. The emergence of MLOps is promising, but many challenges remain. Join our interactive event to hear about the latest developments from Databricks geared toward automating MLOps — including new Git and CI/CD integrations, autologging of experiments, model exp...

Whether it’s enhancing homeland security or building smarter civilian programs, data analytics is the primary driver for digital transformation within the government. A recent McKinsey study estimates data could create value worth $1.2 trillion a year in the Public Sector. However, federal agencies and local governments alike continue to struggle with data silos, the expense of maintaining complicated data architectures, reduced time-to-...

In this live workshop, we’ll cover best practices that bring reliability, performance and security to your data lake and provide the perfect foundation for a cost-effective, highly scalable lakehouse architecture. You’ll learn about the advantages of cloud-based data lakes in terms of security and cost, and how to enable SQL analysts to easily access data in your data lake for reporting and visualization. And finally, learn how to...

In this workshop, we’ll cover best practices to help organizations use powerful open source technologies so you can build and extend your Azure investments and make your data lake analytics-ready. You’ll learn about the advantages of cloud-based data lakes in terms of security and cost. And finally, you’ll learn how data professionals are having a huge impact – lowering costs, changing time to market — and even re...

Machine learning enables organizations to make more informed decisions and predictions at record speed. Cloud computing enables you to tap into a wider variety of data sources to improve the accuracy and speed of these predictions. Join Databricks and Microsoft to learn how to leverage Azure best practices for implementing a complete data science lifecycle, enabling data teams to scale effectively using Azure Databricks, MLflow and other Azure...