Today’s high-tech businesses need agile solutions to work with their evolving modern cloud technologies. In this session, learn how Precisely clients are deploying our solutions in cloud native architectures to take advantage of the scalable, elastic nature of the cloud. We will review example client deployments where Precisely solutions were used for powerful batch processes using Spark within exciting platforms like Databricks and AWS EMR.  During this on-demand webinar, we will also discuss deployment patterns using Kubernetes for scalable, transactional systems that deliver deep business insights to operational and analytical applications.

1. Using Modern Cloud
Technologies to Power
Business Processes
Tim McKenzie

2. Agenda
• Industry Trend Towards Cloud
• Precisely Cloud Deployment Patterns
• Kubernetes Demonstration
• Databricks Demonstration
2

3. Cloud Adoption Forecast
3
More than $1.3 TRILLION in IT spending will
be affected by the shift to the cloud by 2022
Source: Gartner
The public cloud service market is expected
to reach $206.2 billion in 2019 worldwide
Source: Forbes
83% of enterprise workloads will be in the cloud by 2020
Source: Forbes
94% of enterprises already use a cloud service
Source: Flexera
30% of all IT budgets are allocated to cloud computing
Source: Forbes
66% of enterprises already have a central cloud team
or a cloud center of excellence
Source: RightScale
Organizations leverage almost 5 different
cloud platforms on average
Source: Forbes
50% of enterprises spend more than $1.2 million
on cloud services annually
Source: Datometry

4. Companies Are Creating Corporate Strategic
Initiatives to Move to the Cloud…. Why?
1. Reduce Costs - Close Data Centers and Move to Cloud
2. Business Agility- Competitive Advantage
3. Centralized Data Storage/ Access
4. Digital Customer Engagement
5. Realtime Data Collection
6. Rapid Prototyping via Machine Learning
7. Deliver New Insights with Data-Enriched AI Frameworks
4

5. Data is exploding!
5
Business Trends
• Digital Transformation
• Location Intelligence
• Data Science
• Artificial Intelligence
• Machine Learning
Technical Trends
• Data choke point
• 40 zettabytes in 2020
• 5G & IoT – surveillance
• Container technology
Demand for cloud-based analytics at scale
is growing in all industries

6. Leveraging location brings
together business data
• 53% of enterprises say that Location Intelligence is either critically
important or very important to achieving their goals*
• Product Managers need to consider how adding Location
Intelligence can improve the contextual accuracy of marketing, sales,
and customer service apps and platforms
• Marketers need to look at how they can capitalize on smartphones’
prolific amounts of location data for improving advertising, buying,
and service experiences for customers
• R&D, Operations, and Executive Management lead all other
departments in their adoption and use of Location Intelligence
this year
Use the common thread of location to
connect data across your organization
* Louis Columbus Senior Contributor February 16, 2020 Forbes

7. How does geospatial data inform business decisions?
Real Estate
What house is
best for me?
Insurance
What is the
risk at a given
location?
Telecom
Where do I
make network
investments?
Retail
What is the
optimized
product mix at
each store
location?
Healthcare
Do I have
enough care
for my
constituents?
Banking
Where is this
transaction
coming from?

8. Challenges for Data Science
Massive Scale
• Building Footprints:
Available for 100M+ US
properties
• Property Attributes: Across
3000 US counties
• People Data: Thousands
of Demographic Attributes
Unique Data Types
• Addresses, Lat/Lon,
Shapes, Lines, Formats
• Difficult to join different
Formats and Data Types
with accuracy
• Data types must be
modified to be used in
ML algorithms
Geospatial Calculations
• Computationally Intense
to Join and Enrich Spatial
Data at Scale
• Enriching with routing and
catchment is critical, but
highly time consuming

9. A strategy for operationalizing location.
03.
Analyze
Apply Data Science
at scale to gain a
competitive advantage.
02.
Enrich
Leverage trusted ID
to join massive amounts
of your own and 3rd party
data sources .
01.
Organize
Assign a trusted ID
that is unique and
persistent to each address.

10. Business
Locations
Location Risk
Data
Consumer
Demographics
Property
Attributes
Admin
Boundaries
Building
Footprints
Add your data to analytics
PreciselyID
MLS Listings
Signal
Strength
Rating
Territory
3rd Party Data
Historical
Claims
Lifetime
Customer
Value

11. 11
Precisely Big Data/ Cloud SDKs
Leverage cloud native solutions to create scalable location intelligence.
Component Features
Global Addressing &
Geocoding
• Address Validation
• Forward and Reverse geocoding
• Unique and Persistent Address Key
Spatial Processing
• Geohash ID Assignment
• Point and polygon
• Spatial join
• Distance to point, shape, line
Street Routing
• Isochrone/Isodistance
• Walk time/drive time
• Point-to-Point calculations

12. Realtime Address Validation Microservice
Address Validation plus Geocoding and Type-Ahead Service
Configuration Map
Geocoding Preferences
Persistent File Share
Global Address Points Reference
Geocoding Rest
APIs
Container
Registry
Application
Servers
Applications
Persistent File Share
Global Streets Reference Data
Persistent File Share
Interactive Reference Data
Global Address Validation
Service with Geocoding
Rest API Pod
Horizontal Pod Autoscaler
Horizontal Pod Autoscaler
Horizontal Pod Autoscaler
Global Reverse Geocoding
Service
Rest API Pod
Global Interactive Type-Ahead
Rest API Pod
Configuration Map
Reverse Geocoding Preferences
Configuration Map
Interactive Geocoding Preferences
Web
Servers
Applications

13. Location-enabled Lakehouse
Competitor News & Social
Connected Devices
Data Aggregators
Weather
Sales and Policies
IoT Sensors
Data Lakehouse
Geocoding and location
intelligence capabilities to
organize and enrich your data
Video & Images
All of your sources
Any structure
or frequency
Analytics capabilities for
any use case or persona
Ad Hoc Data Science
Low-cost, rapid experimentation with
new data and models.
Explainable Machine Learning
High volume, fine-grained analysis at scale
served in the tightest of service windows.
BI Reporting & Dashboarding
Power real-time dashboarding directly,
or feed data to a data warehouse for
high-concurrency reporting.
Real-time Applications
Provide real-time data to downstream
applications or power applications via APIs..
PreciselyID
CONNECTED
DEVICES/IOT
VIDEO/
AERIAL IMAGERY
CONCENTRATION
OF RISK
WEATHER
EVENTS
HAZARD &
RISK DATA
AMENITIES &
COMPETITION
CUSTOMERS
NETWORK
OUTAGES
PROPERTY
ATTRIBUTES
SCHOOLS &
NEIGHBORHOODS
POPULATION
DEMOGRAPHICS
PARCELS &
BUILDINGS

14. Kubernetes and Databricks
Demonstration

15. Thank You!