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Five Ways Microsoft Helps you do Amazing Things with Data in the Cloud

1: Build data-driven apps that learn and adapt

Applications show intelligence when they can spot trends, react to events, predict outcomes or recommend choices—often leading to richer customer experiences, improved business process, or addressing issues before they arise. The three key ingredients to creating an intelligent app are:

  1. Ingest data in real time
  2. Query across historical and real-time data
  3. Analyze patterns and make predictions with machine learning

clip_image002With Azure, you can make your applications intelligent by establishing feedback loops, and applying big data and machine learning techniques to classify, predict, or otherwise analyze explicit and implicit signals. Today, apps for consumers and enterprises can deliver greater customer or business benefit by learning from user behavior and other signals.

Pier 1 Imports launched a mobile-friendly pier1.com, making shopping online easier. It enabled the selection of delivery options like direct shipment, picking up products in the local store, or a white-glove delivery option from any mobile device. “Although the Pier 1 Imports brand is the same as it has been for more than 50 years, we are continually getting better at identifying what our customer wants, using Microsoft Azure Machine Learning and resulting data insights,” Sharon Leite, EVP Sales and Customer Experience.

Get started with sample code

If you want to learn more about building an intelligent app, try the AdventureWorks Ski App. This sample application can be used to demonstrate the value of building intelligence into an existing application. Learn more by going to GitHub and watching the application being built here.

2: Run big cognition for human-like intelligence over petabyte scale

Microsoft’s Cognitive Services APIs allow developers to integrate vision, speech, language, knowledge and search APIs into your apps. To run these services over petabyte scale, Microsoft integrated the capabilities directly into Azure Data Lake. You can join emotions from image content with any other type of data you have and do incredibly powerful analytics and intelligence over it. This is what Microsoft calls “Big Cognition.” This goes beyond extracting one piece of cognitive information at a time, understanding an emotion or whether there’s an object in an image. Big Cognition joins all the extracted cognitive data with other types of data, so you can do some really powerful analytics with it.

On a global scale, Azure Data Lake is also being used by Carnival Corp., the world’s largest leisure travel company, which has a total of over 100 ships across 10 global cruise line brands, at its Fleet Operations Centers. “We chose to partner with Microsoft to kick off a project of the Internet of Things, because it was strategic for us to rely on a platform that would allow us to collect, analyse, and display data from sensors in a simple, integrated and immediate way on our ships and make them available both to the officers on board and to our operations centre on the ground,” says Franco Caraffi, IT Marine Systems Director of Costa Cruises.

Get started with sample code

Microsoft has demonstrated Big Cognition at Microsoft Ignite and PASS Summit, by showing a demo in which they used U-SQL inside Azure Data Lake Analytics to process a million images and understand what’s inside those images. You can watch this demo here and try it yourself using a sample project on GitHub or discover more ways to get started with Azure Data Lake on GitHub.

3: Deliver <10ms latency to any customer, anywhere on the planet


Most NoSQL technologies force customers to make binary choices among global performance, availability, and transactional consistency. With Azure DocumentDB, Microsoft’s fully managed NoSQL database service, you get four tunable consistency levels to reduce friction related to tradeoffs and unlock new application patterns previously not possible—without ever trading off availability or <10ms latency, which are guaranteed. For example, session consistency gives an ideal blend of performance and consistency for multitenant applications. Tenants are able to achieve strong consistency within the scope of their own session, without having to trade off performance for other tenants. IoT devices emit events at an extremely high rate. Thus, a scale-out database is required to handle heavy write ingestion to persist the full fidelity of unaggregated streams of events. The events from each generation of device looks slightly different as new capabilities and sensors are added. DocumentDB can uniquely ingest a high write of events with varying schema with automatic indexing—and serve it back out using rich queries with low latency, enabling applications to react with real-time anomaly detection.

Citrix delivers solutions used by more than 400,000 organizations and more than 100 million individuals globally. The Citrix web portal was getting a lot of traffic, which was good news, but it was running into challenges integrating the web identity into its SaaS portals. It turned to Azure Service Fabric and DocumentDB to run its Citrix Identity Platform to deliver against its availability, durability, and performance requirements.

Get started with sample code

There are so many great code samples available on GitHub for DocumentDB that Microsoft aggregated their 10 favorite GitHub samples into a single blog for you. Check out these samples across .NET, Node.js, and Python for an array of app scenarios and start playing with DocumentDB today.


CLICK HERE to read the full article and learn how Microsoft is helping organizations do amazing things with their data in the cloud!


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