Integrating Azure Data Lake with other services in the Microsoft Cortana Intelligence Suite, especially Azure Machine Learning, enables you to build end-to-end advanced analytics solutions and intelligent applications that impact revenue-critical decisions and actions. An end-to-end complete solution involves Azure Event Hub and Azure Stream Analytics to provide highly scalable data ingestion and event processing service, uses ADLS to archive native data, and utilizes ADLA to transform native data into structured data that can be used by Azure ML to develop business insights. Azure ML provides a fully managed cloud service to build, deploy and share advanced analytics, including predictive maintenance, energy demand forecasting, customer profiling, anomaly detection and many other possibilities. Advanced analytics results are stored in Azure SQL Data Warehouse, which provides high-performance query on your structured data. Power BI renders visualization on your streaming data and data in Data Warehouse to show business insights.
The Cortana Analytics Suite (CAS) is made up of different components in Azure, allowing users to custom build an analytical application to suit a wide range of analytics scenarios such as real-time recommendations, customer churn forecasting, fraud detection, and predictive maintenance just to name a few.
Today I'm excited to give the Day 1 keynote at PASS Summit v.20, a gathering of our longtime community of SQL Server users and data professionals. PASS Summit is an amazing chance to see the faces of old and new friends. It's a place to meet with customers and fans to continually learn about their evolving needs and to help us grow as a SQL community and develop the best data platform products in the market. Now more than ever, we are architecting for hybrid, because we are hearing from customers that they will be running data workloads on-premises and in the cloud – rarely just one or the other. We believe that the value Microsoft can add is to provide a great and consistent experience wherever they deploy.
This blog post was co-authored by Ali Ghodsi, CEO, Databricks. The confluence of cloud, data, and AI is driving unprecedented change. The ability to utilize data and turn it into breakthrough insights is foundational to innovation today. Our goal is to empower organizations to unleash the power of data and reimagine possibilities that will improve our world. To enable this journey, we are excited to announce the general availability of Azure Databricks, a fast, easy, and collaborative Apache Spark -based analytics platform optimized for Azure.