The document discusses transforming businesses through data-driven insights using Azure advanced analytics and AI, detailing key benefits and services offered by Microsoft Azure. It highlights success stories, such as Lennox International's improvements in data processing accuracy with Azure Databricks, and emphasizes the growing necessity for AI integration in business processes across various industries. The presentation outlines the support and tools available to organizations for leveraging advanced analytics and AI in their operations.

1. Transforming your business through data
driven insights and action - with Azure
Advanced Analytics and Artificial Intelligence
David J. Rosenthal
VP & GM, Digital Business
& Microsoft Partner Commercial
Executive
Microsoft MTC New York City
September 18, 2018

2. Agenda
What is Business Analytics & AI?
Why Azure?
What is the lowest risk path to
Azure AA & AI?
How can Microsoft and Razor
Technology help?
What are others saying?
How do you participate?

5. DataCloud Intelligence

6. 1920 1980s 2010s 2020s
Source: Yale Professor Richard Foster
Average lifespan of a company on S&P 500

7. Cognitive understanding Conversation as a platform

8. $100MThe most digitally transformed enterprises
generate on average $100 million in additional
operating income each year
Source: Keystone Strategy 2016
businesses commercializing data by 2020
10%
higher average net
income on revenue
more revenue per employee
operating marginNEARLY
DOUBLE
$40k
50%+

9. Apps + insights
Social
LOB
Graph
IoT
Image
CRM
Cloud
On-premises Edge
A I B U I LT - I NFA S T & A G I L E E N T E R P R I S E P R O V E N

10. Azure AI Services
Azure Infrastructure
Tools

11. Azure Machine Learning
Cognitive Services
Bot Service

12. { Your Code }
Direct Line Protocol
REST Endpoint

14. Bot builder Platform Intelligence

15. Vision Speech KnowledgeLanguage LabsSearch

17. Spark
SQL Server
Virtual machines
GPUs
Container services
Notebooks
IDEs
Azure Machine Learning Workbench
SQL Server
Machine Learning Server
O N - P R E M I S E S
E D G E C O M P U T I N G
Azure IoT Edge
Experimentation and
Model Management
A Z U R E

18. Local machine
Scale up to DSVM
Scale out with Spark on HDInsight
Azure Batch AI (Coming Soon)
ML Server
Command line tools
IDEs
Notebooks in Workbench
VS Code Tools for AI

19. Single node deployment
(cloud/on-prem)
Azure Container Service
Azure IoT Edge
Microsoft ML Server
Spark clusters
SQL Server

20. Innovation up and costs
down with move to Azure
Benefits realized
Reduced total annual costs, including
maintenance and depreciation, by
about 45% by migrating to Azure
Used services like Azure Machine
Learning and Azure Cognitive Services
to spur digital innovation and boost
customer engagement
Read more
“With the hybrid environment, we have the flexibility to
place our applications and data on the appropriate cloud,
based on our business, technology, and regulatory needs.
Because we can manage our standard and legacy
platforms as a single entity, we can continue our migration
over time as applications evolve and our needs change.”
Tan Kok Meng, Chief Information Officer
Malaysia Airlines

21. AI core infrastructure
AI compute
AI on data

22. Best of Databricks Best of Microsoft
Designed in collaboration with the founders of Apache Spark
One-click set up; streamlined workflows
Interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.
Native integration with Azure services (Power BI, SQL DW, Cosmos DB, Blob Storage)
Enterprise-grade Azure security (Active Directory integration, compliance, enterprise -grade SLAs)

23. Optimized Databricks Runtime Engine
DATABRICKS I/O SERVERLESS
Collaborative Workspace
Cloud storage
Data warehouses
Hadoop storage
IoT / streaming data
Rest APIs
Machine learning models
BI tools
Data exports
Data warehouses
Azure Databricks
Enhance Productivity
Deploy Production Jobs & Workflows
APACHE SPARK
MULTI-STAGE PIPELINES
DATA ENGINEER
JOB SCHEDULER NOTIFICATION & LOGS
DATA SCIENTIST BUSINESS ANALYST
Build on secure & trusted cloud Scale without limits

24. Microsoft Azure Databricks
“At Lennox International, we have 1000’s of devices streaming data
back into our IoT environment. With Azure Databricks, we moved from
60% accuracy to 94% accuracy on detecting equipment failures. Using
Azure Databricks has opened the flood gates to all kinds of new use
cases and innovations. In our previous process, 15 devices, which
created 2 million records, took 6 hours to process. With Azure
Databricks, we are able to process 25,000 devices – 10 billion records –
in under 14 minutes.”
Lennox International is a global leader in the heating, air
conditioning, and refrigeration markets.
Sunil Bondalapati, Director of IT, Lennox International

25. Open deep learning framework support
Visual Studio Tools for AI
Azure Machine Learning Workbench
Azure Machine Learning Studio

26. Visual Studio extension with deep
integration to Azure ML
End to end development
environment, from new project
through training
Support for remote training
Job management
On top of all of the goodness of
Visual Studio (Python, Jupyter, Git,
etc)

27. Windows and Mac based
companion for AI development
Full environment set up (Python,
Jupyter, etc)
Embedded notebooks
Run History and Comparison
experience
New data wrangling tools

28. Platform for emerging data scientists
to graphically build and deploy
experiments
• Rapid experiment composition
• > 100 easily configured modules
for data prep, training, evaluation
• Extensibility through R & Python
• Serverless training and
deployment
Some numbers:
• 100’s of thousands of deployed
models serving billions of requests

29. INGEST STORE PREP & TRAIN MODEL & SERVE
Azure Blob Storage
Logs (unstructured)
Azure Data Factory
Azure Databricks
Microsoft Azure also supports other Big Data services like Azure HDInsight and Azure Data Lake to allow customers to tailor the above architecture to meet their unique needs.
Media (unstructured)
Files (unstructured)
PolyBase
Business/custom apps
(structured)
Azure SQL Data
Warehouse
Azure Analysis
Services
Power BI

30. INGEST STORE PREP & TRAIN MODEL & SERVE
Cosmos DB
Business/custom apps
(structured)
Files (unstructured)
Media (unstructured)
Logs (unstructured)
Azure Blob StorageAzure Data Factory Azure SQL Data
Warehouse
Azure Analysis
Services
Power BI
PolyBase
SparkR
Azure Databricks
Microsoft Azure also supports other Big Data services like Azure HDInsight, Azure Machine Learning and
Azure Data Lake to allow customers to tailor the above architecture to meet their unique needs.
Apps

31. INGEST STORE PREP & TRAIN MODEL & SERVE
Sensors and IoT
(unstructured)
Apache Kafka for
HDInsight
Cosmos DB
Files (unstructured)
Media (unstructured)
Logs (unstructured)
Azure Blob StorageAzure Data Factory
Azure Databricks
Real-time apps
Business/custom apps
(structured)
Azure SQL Data
Warehouse
Azure Analysis
Services
Power BI
Microsoft Azure also supports other Big Data services like Azure IoT Hub, Azure Event Hubs, Azure Machine Learning, and Azure Data Lake
to allow customers to tailor the above architecture to meet their unique needs.
PolyBase

32. demo

33. Intelligent Trusted Flexible

35. 95% Customer interactions
powered by AI bots including
telephone and online by 2025
Engage customers
Build a loyal customer base
with a 24/7 customer-centric
approach to your business
Empower employees
Increase employee productivity and
allow for focus on innovation by
freeing up time through automation

36. Customer need
Impact

37. 75% Applications including AI
By 2018, 50% of apps will
include some form of AI
App innovation
Infuse AI into existing apps to
improved user experience
Knowledge extraction
Backend-infused applications will
leverage latent value in content

38. Customer need
Impact

39. 85% Enterprises embracing AI
By 2020, 85% of Enterprises will be
using AI on at least one process
Financial Services
Risk Analytics
Fraud Prevention
Customer Next Best Action
Retail
Personalization
Dynamic pricing
Advanced retail planning
Manufacturing
Predictive Maintenance
Operations Automation
Fleets management

40. Banking Health Retail Telco Manufacturing
Sales Marketing Customer
service
HR Finance
Industry
verticals
Business
processes

42. Learning Objectives
Understand what Advanced Analytics and AI
is and learn about potential use cases in your
organization
Learn how to build on the skills you already
have to get started with AA and AI
Learn about Microsoft’s comprehensive
portfolio of AA & AI products and solutions
to create innovative AI applications
Discover what tools, guidance and offers are
available to help you infuse intelligence into
your products and services with confidence

43. Azure AI Services
Azure Infrastructure
Tools

44. 1 2 3
Learn about Microsoft
AA + AI products
Start your AA + AI project,
leverage our expertise
Check out the Azure AI Gallery for
analytics solution templates
https://gallery.azure.ai//https://docs.microsoft.com/
en-us/azure/#ai
<insert your URL>

45. © 2018 Razor Technology, LLC www.razor-tech.com
@DavidJRosenthal
Slideshare
www.razor-tech.com
5 Tower Bridge
300 Barr Harbor Dr., Suite 705
West Conshohocken, PA 19428
www.razor-tech.com
David.Rosenthal@razor-tech.com
Cell: 215.801.4430
Office: 866.RZR.DATA
LETS KEEP IN TOUCH