In April 2016, Microsoft launched a set of new offerings named the Cortana Intelligence Suite (previously called Cortana Analytics Suite). Although the suite by itself is also a product through Cortana Intelligence Solutions, the heart of the Suite lies in all the individual Azure products it combines such as Azure HDInsights, Azure Data Lake, Azure Blob Storage, Azure Machine Learning, Azure Stream Analytics, etc. (see full list below)
Figure 1: Strategic overview of Cortana Intelligence Suite
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The power of the Cortana Intelligence Suite lies in its ability to seamless connect all these individual products and aggregate them into a E2E solution designed to tackle your big data or advanced analytics use-case.
Example: Doing predictive maintenance in a supply-chain environment. For the use-case to work, we'll need to capture the data using Event Hubs, curate the date using Stream Analytics and save the output in Blob storage. From there, we'll apply our Machine Learning algorithm and finally save the output data in an SQL Server. Finally, the visual dashboard for the operators will be build on PowerBI.
The added value of Cortana Suite is that all of above products are combined in the Cortana Suite Solution design and offered to the user at-once (incl. configured connections).
Multiple designed solutions are already outlined on the Cortana online website. From there, clients can get inspiration on use-cases to tackle, read how other clients tackled them and finally get started by either getting hands-on with the respective Azure products or contacting a partner such as element61.
In summary, the Suite thus aggregates a set of individual products. Given the importance of these products we want to stress the key components of most solutions.
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Short description on key Azure products:
- Azure Machine Learning
An accessible but comprehensive tool to build machine learning models. Read more on Azure Machine Learning in our recent insight.
- Azure HDInsight
Allows for fast computations written in Hadoop, Spark, R, HBase or Storm. Its designed to handle any amount of data with the ability to scale up to petabytes on demand.
- Azure Stream Analytics
Designed to offer massively parallel real-time stream processing to get real-time insights from device, sensor, infrastructure and applications data (Internet of Things)
- Azure Data Lake Storage
A highly scalable repository for data with Hadoop compatible access. You get all the qualities of object storage along with the advantages of a file system interface (HDFS) optimized for analytics workloads. It is designed to service multiple petabytes of information while sustaining hundreds of gigabits of throughput. Data Lake Storage extends Blob Storage capabilities and is optimized for analytics workloads.
- Azure Data Lake Analytics
An on-demand analytics job service that allows you to run data transformation and processing jobs that scale to massive datasets instantly.
- Azure SQL Data Warehouse
Offers the known strengths of an SQL Server solution as an integration cloud solution. It lets you independently scale compute and storage and can adapt to your workload automatically to handle up to the most demanding data warehousing workload.
- Azure Data Factory
An orchestrator of data pipelines or data extract, load, and transform (ELT) processes.
- Azure Event Hub
A receiving point for events or data streams such as real-time sensors or IoT-devices. It’s designed for simple, secure, and scalable real-time data ingestion, capable of receiving and processing millions of events per second.
- Power BI
A dashboarding tool for simple but robust visualizations; even in real-time.
- Azure Cognitive Services
APIs, SDKs, and services that allow you to build intelligent algorithms into apps, websites, and bots without having direct AI or data science skills or knowledge. The portfolio of machine learning APIs enable you to easily add cognitive features – such as emotion and video detection; facial, speech, and vision recognition; and speech and language understanding – into your applications.
- Azure Bot Service
Provides a complete bot development environment in which you can build, connect, test, deploy, and manage intelligent bots to naturally interact with your users on a website, app, Skype, Slack, Facebook Messenger, and more.
Although the list is already long, numerous other components of Microsoft Azure will play a crucial role in the end solution. The Azure network currently contains 600+ individual products and depending on the upcoming needs in data science and big data industry, Microsoft will add additional (integrated) products.