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Delivering New Retail
with Microsoft Azure and Azure IoT
Daniel Li
IoT Device & Experience
AGENDA
• New Retail and Connected Consumer Journey
• A New Ecosystem and Transformation Success Factors
• Azure IoT Essentials to Realize Your Retail Initiatives
• Azure IoT Reference Architecture
• Azure IoT Edge
• Azure IoT Central
• Azure Machine Learning
• Azure Dynamic 365
• Next Steps
The scale and pace of change2007 $100,000
2013 $200
2007 $40,000
2014 $100
2007 $550,000
2014 $20,000
2000 $2.7bn
2007 $10m
2014 $1,000
1984 $30
2014 $0.16
2009 $30,000
2014 $80
2007 $499
2015 $10
DNA
Solar
Smartphones
Drones
3D Printing
Industrial
Robots
Sensor (3D)
An astonishing pace of change is accelerating transformation.
Technology is more affordable and accessible than ever before.
2
2
3
3
4
4
5
6
6
8
20
0 2 4 6 8 10 12 14 16 18 20 22
Xiaomi
Snapchat
Airbnb
CloudFlare
Uber
Average Unicorns
Tesla
Cloudera
Facebook
Google
Typical Fortune 500
years
Time to reach $1B valuation or more
Source: World Economic Forum
Demand for
personalization
and
customization
Brands selling
direct-to-
consumer
Buying local
Subscription
models
Managing and
using big data
Activist
investors and
consumers
Globally,
middle class
spending will
triple by 2030
New patterns
of
consumption
New demands as result of Change
on retail
Predict what customers want before they tell you
using predictive analytics solutions to create relevant cross-sell
and upsell opportunities throughout the customer journey
Create a connected consumer journey
Deliver engaging in-store
experiences
Enable information-rich experiences in
store with bots, personalized kiosks,
mobile apps.
Connect with customers at the right
time, right place with the right offers
Gather data from various points of customer
contact to understand customer behaviors and
respond with relevant offers.
Give sales associates the customer data to
deliver a personalized in-store experience. Help
customers with mobile POS, assisted selling,
clientelling, and bot applications on mobile
devices.
A new ecosystem to drive business intelligence,
innovative marketing and sale
It Takes Digital Transformation to Capture New
Demand and Ecosystem
ENGAGE YOUR
CUSTOMERS
to provide relevant
service that
increases loyalty
EMPOWER YOUR
EMPLOYEES
to deliver
differentiated service
and maximize
growth
OPTIMIZE YOUR
OPERATIONS
to build an agile,
insight-driven
organization
TRANSFORM
YOUR PRODUCTS
and create new ways
to deliver value
AGENDA
• New Retail and Connected Customer Journey
• A New Ecosystem and Transformation Success Factors
• Azure IoT Essentials to Realize Your Retail Initiatives
• Azure IoT Reference Architecture
• Azure IoT Edge
• Azure IoT Central
• Azure Machine Learning
• Azure Dynamic 365
• Next Steps
Resource
constrained
devices
Existing IoT
devices
IoT SDK
Solution UX
Application Business Logic
Stream Processing and Analytics
Business
Integration
Connectors
and
Gateway(s)
Edge Gateway
Cloud
Gateway
Data Path
Optional solution component
IoT solution component
IoT SDK
Presentation & Business ConnectivityData Processing, Analytics and ManagementDevice Connectivity
Personal
mobile
devices
IP capable
devices
IoT SDK
Business
systems
Device Provisioning and Management
Azure IoT Reference Architecture
Devices Example: Azure IoT Suite Remote Monitoring
Back end
systems and
processes
Event Hub
Storage blobs CosmosDB
Web/
Mobile App
Stream
Analytics
Logic AppsIoT Hub Web Jobs
C# simulator
Remote Monitoring | Predictive Maintence | Connected Factory
Mainframe
Centralized
1960-1970
Mobile-Cloud
Centralized
2005-2020
Client-Server
Distributed
1980-2000
Edge Intelligence
Distributed
2020-
45%
of IoT created data will be stored,
processed, analyzed and acted
upon at the edge by 2019
5.6 billion
IoT devices will be
connected to an edge
computing solution by 2020
IDC FutureScape Worldwide Internet of Things Predictions, 2016
Things
IoT Pattern
Insights Actions
Cloud
Gateway
Azure IoT Hub
Cloud
Gateway Insights ActionsThings
IoT Pattern + Edge
Tremendous Hardware and Silicon Vendor Incremental Opportunity
Azure IoT Hub
Insights Actions
IoT on the Edge
Symmetry
IoT in the Cloud
Remote monitoring and management
Merging remote data from multiple IoT devices
Infinite compute and storage to train machine learning and
other advanced AI tools
Deploy workloads
as containers via
IoT Edge runtime
Manage devices
and containers
centrally in the
cloud
Secure solution
from chipset to
cloud
Use existing AI,
cloud analytics
or create your
own code
Concepts – Cloud off-load
Modular architecture for cloud
offload
Azure services provide AI
modules provide true edge
analytics
Ecosystem for 3rd party edge
services Azure IoT Edge Runtime
Azure IoT Edge device
Scenario: Find insights locally from telemetry data and only
send insights to the cloud.
Ingest
Module
Format
Module
ML
Insights
Telemetry

Public Preview
Released
Nov ‘17
Azure IoT Edge
Extend cloud services (such as
Stream Analytics and Machine
Learning) to IoT devices
Deploy workloads to the edge
via Docker-compatible
containers
Manage devices and edge
services centrally through Azure
IoT Hub
Enable real-time decision
making
Operate reliably in intermittent
cloud connectivity
Reduce bandwidth and costs by
pre-processing data locally
https://azure.microsoft.com/campai
gns/iot-edge/
• Edge Runtime
• Modules
• Cloud off-load
• Cloud configurability
and monitoring
New skill sets
Time-consuming setup and
integration not for everyone
Higher up-front investment
Building an IoT Solution Can be A Challenge
Homepage
Device
Measurements
Device
Rules
Device
Properties &
Settings
Device
Dashboard
Device
Explorer
Device Sets
Analytics
Device Setup
Microsoft IoT Central
Comprehensive
portfolio
Only hyperscale cloud
vendor to offer SaaS,
PaaS, and hybrid
options for IoT, and a
commitment to
continual innovation
Extensive partner
ecosystem
Industry leaders ready
to collaborate with
your business
Industry-leading
security and privacy
From endpoint and
connection through
to data and the cloud
Large-scale SaaS
experience
Experience of
running and
managing powerful,
user-friendly, scalable
solutions used by
millions of users
worldwide
Open
platform
Any device, OS, data
source, software, or
service
AI and Machine Learning
Delight your customers with
personalized experiences
Empower your workforce to
provide differentiated
customer experiences
Transform your products
and services
Optimize your supply
chain with intelligent
operations
Shoe style XYZ
In-stock at Modern Store!
BUY NOW SHOP
SIMILAR
CHAT
Digital assistant
Product expert alert
It looks like Jane
might need help
CUSTOMER
HISTORY
Women’s Clothing
Intelligent Customer Service
Shoe style XYZ
In-stock at Modern Store!
BUY NOW SHOP
SIMILAR
CHAT
Digital assistant
Shoe style XYZ
In-stock at Modern Store!
BUY NOW SHOP
SIMILAR
CHAT
Digital assistant
Product expert alert
It looks like Jane
might need help
CUSTOMER
HISTORY
Women’s Clothing
Intelligent Customer Service
Proposed production
based on forecasted trends
High-performing
attributes
Blue
Leather
Cross-
body
Recommendation: More blue,
leather, and cross-body styles
Demand forecasting
1 2 3 4 5 6 7
Green clutc
Floral hand
Leather cro
Cross-body
Demand forecasting
Blue
Leather
Cross-
body
Recommendation: More blue,
leather, and cross-body styles
Data Modeling & APIs Clients
Traditional
data
Web data
Big data
API
ML STUDIODATA
Predict Customer Needs with Powerful Tools
Demand forecasting
Predictive maintenance
Vehicle telemetry
Azure Machine
Learning templates
Azure Machine
Learning services
Knowledge
Knowledge
Exploration Service
Top publications
in AI...
Listening…
Search
Bing Search
Fraud prevention
results…
Listening…
Language
Natural Language
Processing
Play today’s
conference call…
Listening…
Add a Natural, Human Touch with Cognitive Services
Speech
Speech-to-text and
text-to-speech service
Convert this text to
speech please…
Listening…
Object
recognition…
Vision
Computer Vision
Listening…
Agent Applications Services Infrastructure
Microsoft AI Portfolio
Cortana Office 365
Dynamics 365
SwiftKey
Pix
Customer Service
and Support
Skype
Calendar.help
Cortana Intelligence
Cognitive Services
Bot Framework
Cortana Devices SDK
Cognitive Toolkit
Azure Machine
Learning
Azure N Series
FPGA
People
立即可用的全通路功能
智慧型預測
產品推薦
強化門市體驗
輕鬆部署與整合
© 2017 Microsoft Corporation. 著作權所有,並保留一切權利。
本文件係依「現狀」提供。文件中提及的資訊及觀點 (包括 URL 及其他網際網路網站參考) 如有變更,恕不另行通知。使用本文件的風險係由個人承擔。
本文件並未提供任何 Microsoft 產品之智慧財產的合法使用權。本文件可供個人複製以用於內部參考用途。某些範例僅供說明之用,純屬虛構,並非影射任何真實的對象。
Microsoft 可提供零售商所需的工具來協助其加快業務執行速度,
進而超越客戶期望,並於今日的競爭環境中搶得先機。
零售用 Dynamics 365 是專為零售商所打造的端對端全通路解決
方案。它可透過整合式平台彙整未連線的資料倉儲,並集中處理
各個層面的業務營運,從行銷到現代化銷售點,皆可一手包辦。
這個解決方案能與現有系統輕鬆整合並迅速部署,以加快實現價
值的速度。它將隨著零售商拓展全球營運版圖,協助其因應多通
路、語言、貨幣和法律實體所衍生的複雜度。這個解決方案坐擁
Microsoft Cloud 的強大威力和彈性,可望協助零售商迅速因應
瞬息萬變的商務需求。
深入了運用零售用 Dynamics 365
推動企業轉型
A Business in Transformation
Microsoft
IoT Central
Azure IoT
Edge
+
Azure IoT
Suite
Microsoft IoT Central
IoT SaaS
Microsoft Connected Field Service
Field Service SaaS
Azure IoT Suite
Remote Monitoring Predictive Maintenance Connected Factory
Device Support Edge Support IoT Services Data & Analytics Services Visualization & Integration Services
Azure IoT
Device
SDKCertified Devices
Azure Certified
for IoT
Security Program
For Azure IoT
Windows 10
IoT Core
Azure IoT Edge Azure IoT Hub
Azure IoT Hub
Device Provisioning
Service
Azure Stream
Analytics
Azure Time
Series Insights
Azure
Machine Learning
Cosmo DB
Azure HD Insights,
Spark, Storm
Kafka
Azure Event Hub
Azure Data Lake
Analytics
Azure Data Lake
Microsoft Flow
Azure Logic
Apps
Notification
Hub
Azure
Websites
Microsoft
Power BI
Azure Active
Directory
Azure
Monitor
Partnership is Our Proud Differentiation
ML POC Platform Migration Repeatable Sale
Pilot Implementation Migration & Expansion Re-sell/Co-sell
Stage
Engagement
Phases
Time
Partner
Topline
Projection
Milestone A
PaaS/IaaS
Migration
Milestone B
SEA
Expansion
Machine
Learning
PaaS/IaaS
Migration
Next Gen Device
& IoT Hub
.Data migration onto SQL Azure (extract, cleanse, load)
.ML additional features
.Converge core operation platform on Azure
.Continuous updates to ML and BI embedded to support usage
.Historical data ETL
.Data Scientist
.Partner DevOps
.Partner feature
implementation
.Prelim assessment
.Partner leadership buy-in
.3G operator rate plan
. ARM and x86 cores
. Gaps in device mgmt. &
provisioning
. Server and service migration
.Traffic manager
. Azure SQL – Link to ML modules
. Process for update, dev and production update roll-out
. Next gen Win10IoT in various platforms
. IoT Hub/Event Bus and front end device management trials
(Corp product schedule dependent)
. Local certification assistance
. Multi-tenant operation platform
. Multi-factor authentication
Illustration Purpose Only
Next steps
 Developer
 Build your Edge to connect IoT Hub
 Attach your device onto IoT Central
 Decision maker
 Understand Azure IoT, AI and Dynamic
365 roles in transformation
 Work with Microsoft for a jumpstart
 Azure IoT Edge – http://aka.ms/iot-edge
 Azure Toolkit for Azure IoT Edge Here
 Azure IoT Central - http://aka.ms/iot-central
 Learn more about our vision for digital
transformation at microsoft.com/retail

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Azure IoT - A Practical Entry to New Retail

  • 1. Delivering New Retail with Microsoft Azure and Azure IoT Daniel Li IoT Device & Experience
  • 2. AGENDA • New Retail and Connected Consumer Journey • A New Ecosystem and Transformation Success Factors • Azure IoT Essentials to Realize Your Retail Initiatives • Azure IoT Reference Architecture • Azure IoT Edge • Azure IoT Central • Azure Machine Learning • Azure Dynamic 365 • Next Steps
  • 3. The scale and pace of change2007 $100,000 2013 $200 2007 $40,000 2014 $100 2007 $550,000 2014 $20,000 2000 $2.7bn 2007 $10m 2014 $1,000 1984 $30 2014 $0.16 2009 $30,000 2014 $80 2007 $499 2015 $10 DNA Solar Smartphones Drones 3D Printing Industrial Robots Sensor (3D) An astonishing pace of change is accelerating transformation. Technology is more affordable and accessible than ever before. 2 2 3 3 4 4 5 6 6 8 20 0 2 4 6 8 10 12 14 16 18 20 22 Xiaomi Snapchat Airbnb CloudFlare Uber Average Unicorns Tesla Cloudera Facebook Google Typical Fortune 500 years Time to reach $1B valuation or more Source: World Economic Forum
  • 4. Demand for personalization and customization Brands selling direct-to- consumer Buying local Subscription models Managing and using big data Activist investors and consumers Globally, middle class spending will triple by 2030 New patterns of consumption New demands as result of Change on retail
  • 5. Predict what customers want before they tell you using predictive analytics solutions to create relevant cross-sell and upsell opportunities throughout the customer journey Create a connected consumer journey Deliver engaging in-store experiences Enable information-rich experiences in store with bots, personalized kiosks, mobile apps. Connect with customers at the right time, right place with the right offers Gather data from various points of customer contact to understand customer behaviors and respond with relevant offers. Give sales associates the customer data to deliver a personalized in-store experience. Help customers with mobile POS, assisted selling, clientelling, and bot applications on mobile devices.
  • 6. A new ecosystem to drive business intelligence, innovative marketing and sale
  • 7. It Takes Digital Transformation to Capture New Demand and Ecosystem ENGAGE YOUR CUSTOMERS to provide relevant service that increases loyalty EMPOWER YOUR EMPLOYEES to deliver differentiated service and maximize growth OPTIMIZE YOUR OPERATIONS to build an agile, insight-driven organization TRANSFORM YOUR PRODUCTS and create new ways to deliver value
  • 8. AGENDA • New Retail and Connected Customer Journey • A New Ecosystem and Transformation Success Factors • Azure IoT Essentials to Realize Your Retail Initiatives • Azure IoT Reference Architecture • Azure IoT Edge • Azure IoT Central • Azure Machine Learning • Azure Dynamic 365 • Next Steps
  • 9. Resource constrained devices Existing IoT devices IoT SDK Solution UX Application Business Logic Stream Processing and Analytics Business Integration Connectors and Gateway(s) Edge Gateway Cloud Gateway Data Path Optional solution component IoT solution component IoT SDK Presentation & Business ConnectivityData Processing, Analytics and ManagementDevice Connectivity Personal mobile devices IP capable devices IoT SDK Business systems Device Provisioning and Management Azure IoT Reference Architecture
  • 10. Devices Example: Azure IoT Suite Remote Monitoring Back end systems and processes Event Hub Storage blobs CosmosDB Web/ Mobile App Stream Analytics Logic AppsIoT Hub Web Jobs C# simulator Remote Monitoring | Predictive Maintence | Connected Factory
  • 11. Mainframe Centralized 1960-1970 Mobile-Cloud Centralized 2005-2020 Client-Server Distributed 1980-2000 Edge Intelligence Distributed 2020- 45% of IoT created data will be stored, processed, analyzed and acted upon at the edge by 2019 5.6 billion IoT devices will be connected to an edge computing solution by 2020 IDC FutureScape Worldwide Internet of Things Predictions, 2016
  • 12.
  • 14. Cloud Gateway Insights ActionsThings IoT Pattern + Edge Tremendous Hardware and Silicon Vendor Incremental Opportunity Azure IoT Hub Insights Actions
  • 15. IoT on the Edge Symmetry IoT in the Cloud Remote monitoring and management Merging remote data from multiple IoT devices Infinite compute and storage to train machine learning and other advanced AI tools
  • 16. Deploy workloads as containers via IoT Edge runtime Manage devices and containers centrally in the cloud Secure solution from chipset to cloud Use existing AI, cloud analytics or create your own code
  • 17. Concepts – Cloud off-load Modular architecture for cloud offload Azure services provide AI modules provide true edge analytics Ecosystem for 3rd party edge services Azure IoT Edge Runtime Azure IoT Edge device Scenario: Find insights locally from telemetry data and only send insights to the cloud. Ingest Module Format Module ML Insights Telemetry
  • 18.  Public Preview Released Nov ‘17 Azure IoT Edge Extend cloud services (such as Stream Analytics and Machine Learning) to IoT devices Deploy workloads to the edge via Docker-compatible containers Manage devices and edge services centrally through Azure IoT Hub Enable real-time decision making Operate reliably in intermittent cloud connectivity Reduce bandwidth and costs by pre-processing data locally https://azure.microsoft.com/campai gns/iot-edge/ • Edge Runtime • Modules • Cloud off-load • Cloud configurability and monitoring
  • 19. New skill sets Time-consuming setup and integration not for everyone Higher up-front investment Building an IoT Solution Can be A Challenge
  • 29. Microsoft IoT Central Comprehensive portfolio Only hyperscale cloud vendor to offer SaaS, PaaS, and hybrid options for IoT, and a commitment to continual innovation Extensive partner ecosystem Industry leaders ready to collaborate with your business Industry-leading security and privacy From endpoint and connection through to data and the cloud Large-scale SaaS experience Experience of running and managing powerful, user-friendly, scalable solutions used by millions of users worldwide Open platform Any device, OS, data source, software, or service
  • 30. AI and Machine Learning
  • 31. Delight your customers with personalized experiences Empower your workforce to provide differentiated customer experiences Transform your products and services Optimize your supply chain with intelligent operations Shoe style XYZ In-stock at Modern Store! BUY NOW SHOP SIMILAR CHAT Digital assistant Product expert alert It looks like Jane might need help CUSTOMER HISTORY Women’s Clothing Intelligent Customer Service Shoe style XYZ In-stock at Modern Store! BUY NOW SHOP SIMILAR CHAT Digital assistant Shoe style XYZ In-stock at Modern Store! BUY NOW SHOP SIMILAR CHAT Digital assistant Product expert alert It looks like Jane might need help CUSTOMER HISTORY Women’s Clothing Intelligent Customer Service Proposed production based on forecasted trends High-performing attributes Blue Leather Cross- body Recommendation: More blue, leather, and cross-body styles Demand forecasting 1 2 3 4 5 6 7 Green clutc Floral hand Leather cro Cross-body Demand forecasting Blue Leather Cross- body Recommendation: More blue, leather, and cross-body styles
  • 32. Data Modeling & APIs Clients Traditional data Web data Big data API ML STUDIODATA Predict Customer Needs with Powerful Tools Demand forecasting Predictive maintenance Vehicle telemetry Azure Machine Learning templates Azure Machine Learning services
  • 33. Knowledge Knowledge Exploration Service Top publications in AI... Listening… Search Bing Search Fraud prevention results… Listening… Language Natural Language Processing Play today’s conference call… Listening… Add a Natural, Human Touch with Cognitive Services Speech Speech-to-text and text-to-speech service Convert this text to speech please… Listening… Object recognition… Vision Computer Vision Listening…
  • 34. Agent Applications Services Infrastructure Microsoft AI Portfolio Cortana Office 365 Dynamics 365 SwiftKey Pix Customer Service and Support Skype Calendar.help Cortana Intelligence Cognitive Services Bot Framework Cortana Devices SDK Cognitive Toolkit Azure Machine Learning Azure N Series FPGA People
  • 35. 立即可用的全通路功能 智慧型預測 產品推薦 強化門市體驗 輕鬆部署與整合 © 2017 Microsoft Corporation. 著作權所有,並保留一切權利。 本文件係依「現狀」提供。文件中提及的資訊及觀點 (包括 URL 及其他網際網路網站參考) 如有變更,恕不另行通知。使用本文件的風險係由個人承擔。 本文件並未提供任何 Microsoft 產品之智慧財產的合法使用權。本文件可供個人複製以用於內部參考用途。某些範例僅供說明之用,純屬虛構,並非影射任何真實的對象。 Microsoft 可提供零售商所需的工具來協助其加快業務執行速度, 進而超越客戶期望,並於今日的競爭環境中搶得先機。 零售用 Dynamics 365 是專為零售商所打造的端對端全通路解決 方案。它可透過整合式平台彙整未連線的資料倉儲,並集中處理 各個層面的業務營運,從行銷到現代化銷售點,皆可一手包辦。 這個解決方案能與現有系統輕鬆整合並迅速部署,以加快實現價 值的速度。它將隨著零售商拓展全球營運版圖,協助其因應多通 路、語言、貨幣和法律實體所衍生的複雜度。這個解決方案坐擁 Microsoft Cloud 的強大威力和彈性,可望協助零售商迅速因應 瞬息萬變的商務需求。 深入了運用零售用 Dynamics 365 推動企業轉型
  • 36. A Business in Transformation
  • 38. Microsoft IoT Central IoT SaaS Microsoft Connected Field Service Field Service SaaS Azure IoT Suite Remote Monitoring Predictive Maintenance Connected Factory Device Support Edge Support IoT Services Data & Analytics Services Visualization & Integration Services Azure IoT Device SDKCertified Devices Azure Certified for IoT Security Program For Azure IoT Windows 10 IoT Core Azure IoT Edge Azure IoT Hub Azure IoT Hub Device Provisioning Service Azure Stream Analytics Azure Time Series Insights Azure Machine Learning Cosmo DB Azure HD Insights, Spark, Storm Kafka Azure Event Hub Azure Data Lake Analytics Azure Data Lake Microsoft Flow Azure Logic Apps Notification Hub Azure Websites Microsoft Power BI Azure Active Directory Azure Monitor
  • 39.
  • 40. Partnership is Our Proud Differentiation ML POC Platform Migration Repeatable Sale Pilot Implementation Migration & Expansion Re-sell/Co-sell Stage Engagement Phases Time Partner Topline Projection Milestone A PaaS/IaaS Migration Milestone B SEA Expansion Machine Learning PaaS/IaaS Migration Next Gen Device & IoT Hub .Data migration onto SQL Azure (extract, cleanse, load) .ML additional features .Converge core operation platform on Azure .Continuous updates to ML and BI embedded to support usage .Historical data ETL .Data Scientist .Partner DevOps .Partner feature implementation .Prelim assessment .Partner leadership buy-in .3G operator rate plan . ARM and x86 cores . Gaps in device mgmt. & provisioning . Server and service migration .Traffic manager . Azure SQL – Link to ML modules . Process for update, dev and production update roll-out . Next gen Win10IoT in various platforms . IoT Hub/Event Bus and front end device management trials (Corp product schedule dependent) . Local certification assistance . Multi-tenant operation platform . Multi-factor authentication Illustration Purpose Only
  • 41. Next steps  Developer  Build your Edge to connect IoT Hub  Attach your device onto IoT Central  Decision maker  Understand Azure IoT, AI and Dynamic 365 roles in transformation  Work with Microsoft for a jumpstart  Azure IoT Edge – http://aka.ms/iot-edge  Azure Toolkit for Azure IoT Edge Here  Azure IoT Central - http://aka.ms/iot-central  Learn more about our vision for digital transformation at microsoft.com/retail