Using Azure Machine Learning with an on-premises Database - SQLServerCentral


With Azure Machine Learning (AzureML) you have access to a cloud based, flexible and friendly method to perform machine learning tasks on your data. One disadvantage I frequently run into is that cloud based approach of AzureML since the data you are building your machine learning models on has to be in the cloud as well. Even though AzureML offers a variety of ways to access your data, from CSVs to Azure Blob Storage and Azure SQL Database, having to store data in the cloud is one of the major drawbacks me, and some of my clients, run into. But there is good news! The Data Management Gateway acts like a bridge between AzureML and your on-premises SQL Server databases allowing you to import data directly from a local database!

Microsoft Partners with Adobe on Dynamics 365 - Petri


Microsoft announced today that it will make Adobe Marketing Cloud the preferred marketing service for its Dynamics 365 Enterprise offering. The new partnership will give customers a powerful, comprehensive marketing service for intelligent business applications, Microsoft says. First announced in July ahead of its Worldwide Partner Conference, Microsoft Dynamics 365 will become available to customers in the coming weeks. It is a new, Azure cloud-hosted combination of the software giant's CRM (customer relationship management) and ERP (enterprise resource management) solutions. The goal is clear enough: To modernize these capabilities and bring them to market as a public cloud business management service.

Harness the future with the ultimate hybrid platform for data and AI


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.

Why (and how) Microsoft is circling its hybrid-cloud wagons


If expectations pan out, Amazon and VMware will announce today a tie-up that will give Amazon a hybrid-cloud computing play (at long last). Perhaps not so coincidentally, Microsoft, which has been touting hybrid computing as a key differentiator for the company for years, is stepping up its hybrid-cloud rhetoric as of late. As far and fast as cloud computing is embedding itself into the enterprise, there remain many cloud-resistant applications and services. For years, Amazon officials referred to private cloud as the "false cloud," claiming that any and every workload should be in the public cloud. For just as long, Microsoft officials have made the case that users should be able to decide which of their workloads belonged on premises, in the public cloud and/or in some type of hybrid configuration.

Splice Machine Data Platform for Intelligent Apps Launches on Azure


San Francisco-based startup Splice Machine, whose database management system is specifically optimized for hybrid clouds, on July 11 announced the availability of its automated application platform on the Microsoft Azure cloud service. Splice Machine's Online Predictive Processing Platform (OLPP) is designed to power new-generation predictive analytics applications that run both on premises and in the cloud--or multiple clouds--as needed in production requirements. Becoming available on the growing Microsoft Azure cloud service gives admins another way to use the data platform while having the independence to deploy on premises, on Amazon Web Services, Azure, or both, the company said. Using Splice Machine, the company claims, enterprises can develop and deploy smarter predictive applications that integrate integrate fast data streaming, transactional workloads, analytics and machine learning, enabling business transformation at performance and scale. Using Splice Machine's cloud service replaces or offloads traditional and cloud-based RDBMS and cloud-based or on-premises data warehouse packages.