O documento discute a Internet das Coisas (IoT) e computação em nuvem, explicando como os dispositivos são conectados através da nuvem e como os dados são armazenados e analisados para fornecer informações e tomar ações. A nuvem permite recursos de TI escaláveis e serviços on-demand para vários clientes.
14. Cloud Computing
A Computação em Nuvem é um
estilo de computação em que
recursos de TI altamente escaláveis
são fornecidos como um serviço
usando tecnologias de Internet a
vários clientes externos
15.
16. O conceito é tão antigo quanto a própria internet
Previsão
Virtualização
Essa é a base
da nuvem
A computação
será distribuída
como serviço
34. Devices Device Connectivity Storage Analytics Presentation & Action
Event Hubs SQL Database
Machine
Learning
App Service
Service Bus
Table/Blob
Storage
Stream
Analytics
Power BI
External Data
Sources
DocumentDB HDInsight
Notification
Hubs
External Data
Sources
Data Factory Mobile Services
BizTalk Services
{ }
35. Azure IoT services
Accelerate your business transformation
Azure IoT Suite
Predictive MaintenanceRemote Monitoring Asset Management
And more…
Addresses
common
scenarios:
Enables
you to Mine data Take actionConnect assets
M o n i t o r i n g
36. Partnering in the cloud era
New ‘cloud friendly’ protocols
using XML/JSON & HTTP
Leveraging partners across
the globe
Quick and simple partner
onboarding
Leverage on-demand scaling
to better utilize resources
37. Why the Internet of Things matters
Redefine
customer
service
Open new
business
opportunities
Build
competitive
edge
Gain insight
and agility
46. Reference Data Seamless correlation of event streams
with reference data
Static or slowly-changing data stored in blobs
CSV and JSON files in Azure Blobs;
scanned for new snapshots on a settable cadence
JOIN (INNER or LEFT OUTER) between streams and
reference data sources
Reference data appears like another input:
SELECT myRefData.Name, myStream.Value
FROM myStream
JOIN myRefData
ON myStream.myKey = myRefData.myKey
47. Partitioning allows for
parallel execution over
scaled-out resources
SELECT Count(*) AS Count, Topic
FROM TwitterStream PARTITION BY PartitionId
GROUP BY TumblingWindow(minute, 3), Topic, PartitionId
Query Result 1
Query Result 2
Query Result 3
Event Hub
55. Machine Learning Azure ML and Stream Analytics are
now integrated
The integration is in limited preview as of today!
(See team blog for sign-up information.)
Azure ML can publish web endpoints for
operationalized models
Azure Stream Analytics can bind custom function
names to such web endpoints
Example: apply bound function event-by-event
mapped to endpoint/API key
SELECT text, sentiment(text) AS score
FROM myStream
56. Easy to Train | Out of the Box alg. | Easy to Deploy