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The retail industry has changed dramatically over the past few years due to supply chain disruptions, economic fluctuations, and changing customer demands. Discover the latest Microsoft 365 and Teams innovations that we’ll be showcasing at NRF here.
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Now more than ever, IT leaders need to reduce costs while securing and empowering their workforce. Microsoft 365 combines the capabilities organizations need in one secure, integrated experience—powered by data and AI—to help people work better and smarter.
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Commercial and public sector organizations continue to look for new ways to advance their goals, improve efficiencies, and create positive employee experiences. The rise of the digital workforce and the current economic environment compels organizations to utilize public cloud applications to benefit from efficiency and cost reduction.
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Now that hybrid work is just work, the challenge for organizations is to balance employee demands for flexibility with business needs. This month we made improvements to help employees work smarter and more efficiently, with integrated technology that brings people together across every role and function so they can connect and collaborate effectively in the flow of work.
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Overview
The Microsoft Cloud App Security (MCAS) connector lets you stream alerts and Cloud Discovery logs from MCAS into Azure Sentinel. This will enable you to gain visibility into your cloud apps, get sophisticated analytics to identify and combat cyberthreats, and control how your data travels, more details on enabling and configuring the out of the box MCAS connector (Connect data from Microsoft Cloud App Security)
The Microsoft Cloud App Security API provides programmatic access to Cloud App Security through REST API endpoints. Applications can use the API to perform read and update operations on Cloud App Security data and objects.
To use the Cloud App Security API, you must first obtain the API URL from your tenant. The API URL uses the following format:
https://<portal_url>/api/<endpoint>
To obtain the Cloud App Security portal URL for your tenant, do the following steps:
– In the Cloud App Security portal, click the question mark icon in the menu bar. Then, select About.
– In the Cloud App Security about screen, you can see the portal url.
Cloud App Security requires an API token in the header of all API requests to the server, such as the following:
Authorization: Token <your_token_key>
Where <your_token_key> is your personal API token. For more information about API tokens, see Managing API tokens., here’s an example of CURLing MCAS Activity log:
The following table describes the actions supported:
Where Resource represents a group of related entities, fore more details please visit MCAS Activities API
Add For each control to iterate MCAS Activities parsed items:
Select an output from previous steps: @variables(‘TempArrayVar’)
Send the data (MCAS Activity Log) to Azure Sentinel Log analytics workspace via a custom log tables:
JSON Request body: @{items(‘For_each’)}
Custom Log Name: MCAS_Activity_Log
Notes & Consideration
You can customize the parser at the connector’s flow with the required and needed attributed / fields based on your schema / payload before the ingestion process, also you can create custom Azure Functions once the data being ingested to Azure Sentinel
You can customize the for-each step to iterate MCAS Activity log and send them to the Log Analytics workspace so eventually each activity log will be logged in a separate table’s record / row
You can build your own detection and analytics rules / use cases, a couple of MCAS Activities analytics rules will be ready to use at github, stay tuned
Couple of points to be considered while using Logic Apps:
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We are really excited to introduce the preview of new machine learning experiences in Azure Synapse Analytics, to make it easier for data professionals to enrich data and build predictive analytics solutions.
AI and machine learning is an important aspect of any analytics solution. By integrating Azure Synapse Analytics with Azure Machine Learning and Azure Cognitive Services, we are bringing together the best of two worlds, to empower data professionals with the power of predictive analytics and AI. Data engineers working in Azure Synapse can access models in Azure Machine Learning’s central model registry, created by data scientists. Data engineers can also build models with ease in Azure Synapse, using the code-free automated ML powered by Azure Machine Learning and use these models to enrich data.
Linking workspaces to enable collaboration between Data professionals and ML professionals
Linked services can be created to enable seamless collaboration across an Azure Synapse and an Azure Machine Learning workspace. Linked workspaces allow data professionals in Synapse to leverage new machine learning experiences aiming to make it easier to collaborate across Synapse and Azure ML.
Create the Azure Machine Linked service in your Synapse workspace
Seamlessly access Azure Machine Learning models from Synapse
Data professionals working in Azure Synapse can collaborate seamlessly with ML professionals who create models in Azure Machine Learning. These models can be shared and deployed directly in Azure Synapse for enrichment of data.
In the model scoring wizard, enrich with an existing model
By supporting the portable ONNX model format, users can bring a variety of models to Synapse for performant batch scoring, right where the data lives. This removes the need for data movement and ensures that the data remains within the security boundaries defined by Azure Synapse. Columns containing predicted values can easily be appended to the original views and tables that are used to populate your Power BI reports.
Enrich data with Azure Cognitive Services pre-trained models
Fully integrated data enrichment capabilities powered by Azure Cognitive Services allow Synapse users to enrich data and gain insights by leveraging state of the art pre-trained AI models. The first two models available through the Synapse workspace are Text Analytics (Sentiment Analysis) and Anomaly detector. In the future you’ll see more pre-trained models available for use.
Leverage Azure Cognitive Services in Azure Synapse for sentiment analysis
Leverage Azure Cognitive Services in Azure Synapse for Anomaly detection
Train models in Synapse using Automated ML powered by Azure Machine Learning
Data professionals can also build models with ease in Azure Synapse, using code-free automated ML powered by Azure Machine Learning. These Automated ML runs will be executed on Synapse serverless Apache Spark pools and tracked in the Azure Machine Learning service.
Select the task type for your Automated ML run in Azure Synapse
All the machine learning experiences in Azure Synapse produce code artifacts such as PySpark Notebooks or SQL scripts, that allow users of all skill levels to easily operationalize their work in data integration pipelines, to support end-to-end analytics flows from a single unified Synapse experience.
Get started today
We are expanding Azure Synapse to bring together the best in big data analytics and machine learning so you can leverage the full power of Azure. These new experiences in Synapse Studio will streamline the way data teams collaborate and build predictive analytics solutions. A large number of our customers are already taking advantage of predictive analytics solutions. Learn more about how you can get started on your journey with ML experiences in Azure Synapse by using the links provided below.
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