We take you through 10 best practices, considerations, and suggestions that can enrich your Microsoft Teams deployment and ensure both end-user adoption and engagement.
As far back as this year’s Ignite event, Microsoft has been mentioning “Cortana Analytics” by name. But at the first-ever Cortana Analytics Workshop in Redmond this past Sept 10 and 11, they unveiled a bigger offering and vision linking their current slate of cloud-based data platform tools.
It’s known that Microsoft has been using Big Data technology for Exabyte (EB) level storage and search internally for years; this is the story of Bing and building the data underpinnings of a major search engine. Hadoop-based cloud services like HDInsight and the ability to run Linux and Hortonworks HDP on Azure Virtual Machines have made their way to being a part of Microsoft’s offerings for some time now.
But with Cortana Analytics, Microsoft is democratizing this capability using Azure as a delivery platform, and realizing a much fuller vision that Azure and cloud technology now provide. To this back-end data storage backdrop, Microsoft is adding event capture and Internet of Things (IoT) capabilities, plus R-based statistical modeling services in order to provide some very compelling full data lifecycle analytics functionality.
Cortana Analytics refers to a cloud-based ecosystem hosted in Microsoft Azure for building and deploying elastic, scalable modern data warehousing and advanced analytics solutions. The entire data workflow — from event ingest/data capture, to data storage, to analytical processing and transformation, to modeling, to real-world deployment — is covered by a set of cloud-based services are intended to be combined to collect events and data and turn them into actionable intelligence, enabling human or automated action.
So, the Cortana Analytics Suite encompasses a set of these data-oriented Azure PaaS offerings, including:
- Azure Event Hub
- Azure Data Catalog
- Azure Data Factory
- Azure Data Lake
- Azure SQL Data Warehouse
- Azure Stream Analytics
- Azure HDInsight
- Azure Machine Learning
- Power BI
In upcoming posts, I’m going to break these services into functional groups, and try to place them in the context of a hypothetical solution. Next time: We’ll start the series proper with a discussion of Event and Data Ingestion and Storage in Cortana Analytics.