Applications show intelligence when they can spot trends, react to unusual events, predict outcomes or recommend choices. Learn how to introduce intelligence traits into your apps including; establishing feedback loops, applying big data and machine learning techniques to classify, predict or otherwise analyze explicit and implicit signals, and operationalizing the full stack into the regular usage flow of the app. Most every day apps, from consumer to enterprise can deliver greater customer or business benefit by learning from user behavior and other signals. In this session we’ll take a pragmatic look at introducing real, useful data-driven intelligence into apps by walking through services, code and data needed to make it happen.

3. Your app
Intelligent apps
learn and adapt to deliver
more powerful experiences

4. Making an app intelligent
Feedback loops use data
to improve results over time
Your app

5. Add intelligence
to existing apps

6. Add intelligence
to existing apps
Ski rental reservation
Displays products
Handles transactions

7. Add intelligence
to existing apps
Ski rental reservation
Displays products
Handles transactions
With intelligence
Predicts demand to help customers
know what to expect

8. Add intelligence
to existing apps
Lift status
Shows open/closed status

9. Add intelligence
to existing apps
Lift status
Shows open/closed status
With intelligence
Predicts wait time
Warns based on traffic
Identifies anomalies

10. Add intelligence
to existing apps
Dining
Shares menu
Takes reservations

11. Add intelligence
to existing apps
Dining
Shares menu
Takes reservations
With intelligence
Knows where you want to eat next

12. Demo
Pablo Castro
Software Architect
Database Systems Group

13. Architecture
Ski rental

14. Architecture
Lifts and runs

15. Architecture
Dining

16. Today’s
ingredients
for intelligence
Azure Event Hubs
Collect
events
Azure Redis Cache
Azure Data Lake
SQL Server with R
Azure Blob Storage
Store data
Azure SQL Database
Azure DocumentDB
Azure Data Lake
Azure SQL Data Warehouse
R Tools for Visual Studio
Azure Search
Improve the
experience
Azure App Service
Azure Machine Learning
Azure Stream Analytics
Learn
and adapt
Azure HDInsight
Power BI
Cortana Analytics Suite

17. Transform business
with intelligent apps
Demand
Revenue
Growth
Forecasting
Ski rental reservation
Fraud
Supply chain delays
Customer dissatisfaction
Anomaly detection
Lift status
Personalized offers
Cross-channel experiences
Product recommendations
Tailored experiences
Dining

18. Next Monday:
1) Pick an existing app.
2) Start adding in intelligence.
Instrument your app to collect telemetry and start a feedback loop.
See if any Cortana Analytics pre-built models will make your app smarter.
Use AzureML with telemetry data to add an intelligent behavior to your app.
Add search and recommendations to your app.
Try R services for SQL Server 2016 for ETL-free advanced analytics.