This document summarizes how businesses can transform through business intelligence (BI) and advanced analytics using Microsoft's modern BI platform. It outlines the Power BI and Azure Analysis Services tools for visualization, data modeling, and analytics. It also discusses how Collective Intelligence and Microsoft can help customers accelerate their move to a data-driven culture and realize benefits like increased productivity and cost savings by implementing BI and advanced analytics solutions in the cloud. The presentation includes demonstrations of Power BI and Azure Analysis Services.

1. Transforming your business through
Business Intelligence - with Microsoft
Modern BI and Advanced Analytics
CHUCK RUSSELL
Sr. PARTNER
COLLECTIVE INTELLIGENCE INC.

2. Agenda
How can you transform your business
with BI?
What is the Microsoft Modern BI
platform?
Power BI & Power BI Report Server
Azure & SQL Analysis Services
Advanced Analytics
Testimonials
How can Microsoft and Collective
Intelligence Help?
Next Steps?

3. A world of unprecedented change
Average lifespan of a company on S&P 500

5. Making sense of the growing
data universe is critical…
1. Source: IDC “FutureScape: Worldwide Big Data and Analytics 2019 Predictions,” DOC #259835,
November 2015
2. Source: IDC “FutureScape: Worldwide Cloud 2017 Predictions,” DOC #259840,
November 2015
…and that data is
moving to the cloud
3. Source: Gartner “Cost Optimization Secrets: Plan & Manage Cloud Services for 14% Savings, on
Average,” ID: G00299793, March 2017

6. Transforming with data: your opportunity
Extra productivity
benefits by 2020
Additional
operating income
Further
cost savings

7. The modern BI platform

8. MODEL ANALYZE & AUTHOR DELIVER VISUALIZE
End User BISelf-Service BI
Microsoft Business Intelligence

9. Power BI: experience your data
Any data, any way, anywhere

19. Discovery & exploration
Easy report authoring
Custom visualizations
R integration

20. Connect to data in the cloud
and on-premises
Shape, transform, and clean
data for analysis
Join and model data from
multiple sources/types
Extend with advanced
analytics technologies like R

23. Demo: Power BI Overview

24. Demo Path
• Power BI (Cloud) – User Perspective
• Explain Portal Areas / Workspace Etc.,
• Show Reports / Dashboards
• Show Insights
• Discuss Realtime Access versus Stored Data
• Power BI Desktop
• Show Authoring / PowerBI Desktop
• Connecting to Data
• Power BI Model(s)
• Publishing to the Web
• Scheduling Refreshes
• Integrating / Embedding Options
• Excel as Tool of Choice

25. Move to the cloud on your terms
Compatible with SSRS
Power BI Report Server
Self-service BI and enterprise reporting in one solution
Keep Power BI reports on-premises

34. Enterprise grade tools for lifecycle
management
Compatible with major BI tools –
Excel, Power BI, third party
Gain instant insights with in-
memory cache
Build business friendly BI models
Analysis services
Enterprise grade analytics engine —on-premises and in the cloud

35. Azure Analysis Services
Transform complex on-premises or cloud data into insights
Azure Analysis Services

36. Azure Analysis Services
Gain instant insights using your preferred visualization tools
Azure Analysis Services

37. Azure Analysis Services
Proven analytics engine based on SQL Server technology
DAX calculations
Tabular model
In-memory DirectQuery
MDX DAX

38. Platform-as-a-service solution
All the benefits of the cloud in your analytics engine
Azure Analysis Services

39. SQL Server Analysis Services
Enterprise grade analytics engine
10
01
10
01

40. SQL Server 2017+ Analysis Services
Turn data into insights with an enterprise-grade data modeling and
analytics engine
Build user friendly semantic
models for rich semantic models
Quickly gain instant insights using SSAS
in-memory (VertiPaq) technology &
scale to many users
Use your preferred BI tool
to visualize data insights

41. Complex raw data Rich, business user friendly
semantic model
SQL Server Analysis Services
Business user easily
gain insights
Cache
Semantic model Queries
SQL Server 2017 Analysis Services
Transform complex data into one version of the truth

42. Quick Demo:
Power BI & Analysis Services

43. Demo Path
• Demonstrate Azure Analysis Services
• Show Model Management
• Demonstrate Connecting to Azure Analysis Data Source
• Show Realtime Access to Cloud Data / Power BI Desktop

44. Azure AI Services
Azure Infrastructure
Tools

45. Azure Machine Learning
Cognitive Services
Bot Service

46. Vision Speech KnowledgeLanguage LabsSearch

47. 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

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

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

50. AI core infrastructure
AI compute
AI on data

51. 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)

52. 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

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

54. 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)

55. Azure Machine Learning Studio
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

56. 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

57. 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

58. 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

59. Demo Path
• Demo ML Studio
• Describe the Titanic Experiment
• Spin Up DataBricks (time Permitting)

61. Modern BI / Advanced Analytics Customers
Retail &
Consumer Goods
Discrete
Manufacturing
Government
& Education
Professional
Services
Banking & Financial
Services
Healthcare

62. Accelerate your move
towards a Data Culture
Reduce risk / increase ROI as
you move to the cloud
6 Kacey Court, Mechanicsburg, PA
717.545.9730
sales@collectiveintelligence.com
John Schrock
Collective Intelligence
www.collectiveintelligence.com