Microsoft Azure Data Factory
Integrate your data silos with Azure Data Factory. This service is built for all data integration needs at any skill level. Craft ETL and ELT processes within the visual builder or write your own code from scratch. Visually integrate your data sources with ease using native connectors without the need for self-maintenance, at no added cost.
- Build hybrid ETL and ELT pipelines using the Data Factory visual environment with no maintenance required.
- Scale on demand with cost-efficient, fully managed, serverless, cloud data integration.
- Azure security measures protect you across deployment locations, connect to on-premises, cloud-based, and software-as-a-service apps.
- Easily rehost on-premises SQL Server Integration Services packages in the cloud using Microsoft Azure Data Factory.
Azure Machine Learning Studio
Microsoft Azure Machine Learning Studio (classic) is an easy-to-use, collaborative, drag-and-drop tool. You can build, test, and deploy predictive analytics to learn more from your data. Publish your models as web services that can easily be consumed by custom apps or business intelligence tools like Excel.
Provide users with a robust, interactive, visual workspace. You can quickly and easily build, test, and iterate on predictive analysis models. Simply drag-and-drop datasets and prebuilt analysis modules into the interactive canvas. By connecting them together you form an experiment that enables you to iterate on your model design, edit the experiment, save a copy, and run it multiple times. When you’re finished with your model, convert the training experiment to a predictive experiment, and publish it as a web service to make it available to others.
There is no programming required, simply visually connect datasets and modules to build your own predictive analysis model.
Leverage all your data to unlock new insights with artificial intelligence solutions using Azure Databricks. Spin up your Apache Spark™ environments in minutes, scale resources automatically, and collaborate with your team through the interactive workspace. Azure Databricks supports SQL, Python, R, and Java, and data science libraries and frameworks such as TensorFlow, Pytorch, and scikit-learn.
Apache Spark™ is a trademark of the Apache Software Foundation.
Shared workspaces with common languages
Share projects to collaborate using the interactive workspace. Build with your preferred language, supports Python, Scala, R, and SQL. Provide easy version control of your notebooks with GitHub and Azure DevOps.
Accelerate machine learning on big data
Quickly identify the most appropriate algorithms and hyperparameters with integrated Azure Machine Learning to leverage automated machine learning capabilities. Easily manage, monitor, and update learning models deployed in any environment. This solution provides a central registry for all experiments, machine learning pipelines, and models you have deployed.
Modern data warehousing built for speed
Gain unmatched levels of performance and scalability by modernizing your data warehouse in the Azure cloud. Easily combine data at scale to derive new insights with analytical dashboards and operational reports.
Microsoft Power BI
Unify your data from multiple sources to create interactive dashboards and reports that unlock actionable insights to drive business results.
Self-service analytics at any scale
Reduce the added cost, complexity, and security risks of multiple solutions with an analytics platform that scales from the individual to the organization.
Smart tools, smarter results
Find and share meaningful insights with hundreds of data visualizations, built-in AI capabilities, Excel integration, as well as prebuilt and custom data connectors.
Protect your analytics data
Sensitivity classification enables data loss prevention features to keep your data secure and compliant.