Businesses can leverage modern cloud platforms and practices for net-new solutions and to enhance existing capabilities, resulting in an upgrade in quality, increased speed-to-market, global deployment capability at scale, and improved cost transparency. In this webinar, Josh Rachner, data practice lead at Sense Corp, will help prepare you for your analytics transformation and explore how to make the most on new platforms by: Building a strong understanding of the rise, value, and direction of cloud analytics Exploring the difference between modern and legacy systems, the Big Three technologies, and different implementation scenarios Sharing the nine things you need to know as you reach for the clouds You’ll leave with our pre-flight checklist to ensure your organization will achieve new heights.

1. Achieve New Heights with
Modern Analytics
1
Next Gen Capabilities
Deliver In Days & Weeks, Not Months & Years

2. 2
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Practice Lead, Modern Analytics
jrachner@sensecorp.com
Josh Rachner

3. Introduction to Modern Analytics
The rise, value, and direction of cloud analytics

4. Reporting and dashboards evolve, and
Business Intelligence (BI) became the
phrase of the day.
In the marketplace, smaller BI vendors were
acquired by larger companies, while new
market entrants in this space conjured up
amazing data visualizations.
Organizations began leveraging cloud platforms
for data warehousing solutions by initially
deploying their data warehouse software on a
cloud infrastructure using hosted
environments.
The age of the internet yields larger volumes of
data. Organizations began using data
warehouse appliances for processing large
volumes of analytical data.
Organizations begin to evaluate true Data
Warehouse as a Service (DWaaS) solutions that
are fully operated and managed in the cloud.
Organizations are comfortable with having
Application Service Providers (ASPs) host and
maintain their data warehouse applications.
How modern analytics have developed over the years:

5. Months of setup
Primarily on-premises
Mainly structured SQL
Through custom APIs
Row-based; Clustering; Server processing
Batch; Built nightly
Managed by IT
Developed by developers
Days of setup
Data cloud and/or on-premises sources
Near real-time/real-time; Virtualized
Integrated with customer apps/self-service
Created by end users
Infrastructure
Data sources
Data types
Market data
Data storage
Processing
Aggregation
User interface
Visualization
Extract, Transform, Load (ETL); Schema write
Both structured and unstructured: SQL, XML, JSON, Avro,
Parquet, etc.
Extract, Load, Transform (ELT); Schema read
Column-based; Massively Parallel Processing (MPP);
In-Memory processing
Through marketplaces and data exchanges
Legacy Analytics Modern AnalyticsVS.

6. Increase speed
to market
Improve transparency
of costs
Deliver better analytics
service quality
Enhance security
Operate on a
global scale
Increase infrastructure
performance and
operating efficiency
Reduce data
center dependence
Strengthen DevOps
and DataOps
integration
Retain key personnel
and attract new hires
Assess Value Drivers that Fuel Your Journey
Create efficiency gains

7. Comparing Leading Cloud Platforms

8. Data Platform
Data Pipelines
Data Fabric
Data Science
Workbench Data Visualization
Major Players & Up-and-Comers

9. 01
02
03
Big Data & AI/ML POCs and POVs
This is where organizations simply want to explore big data POC technical
feasibility or POV business capability solutions and use the modern analytics
platform to support rapid experimentation.
Migrating and Enhancing Legacy Analytics Solutions
This is where organizations want to move existing legacy analytics to a
modern analytics cloud platform to gain enhanced functionality. The effort is
driven by new data sources as well as trying to improve and enhance existing
analytics capabilities.
Licensing or Contractual Drivers
This is where organizations are battling heavy legacy environment
maintenance costs and wish to explore alternatives. For these organizations,
the primary driver is the requirement to move off the legacy platform as
soon as possible, allowing them to offset and reduce costs.
Value
Rapid experimentation and speed to market
Risk
Uncoordinated efforts can result in disjointed strategy
Value
Improved analytics capabilities with net new use cases
Risk
Ineffective migration strategy, failed/costly initiatives
Value
Use of cost-efficient cloud capabilities
Risk
Hidden cloud pricing can result in increased spend
Key Implementation Scenarios

10. 9 Considerations for Your
Journey to the Cloud

11. 01. Cost & Complexity
 Have you budgeted appropriately?
 Have you planned for additional resources?
 Have you planned for additional vendor management?
02. Hiring & Upskilling
 Have you determined resource and skills needs?
 Have you determined hiring or upskilling needs?
 Have you created a training plan?
03. Budgeting & Procurement
 Have you planned your CAPEX/OPEX shift?
 Have you communicated the change to business units?
 Have you developed an expense allocation plan?
04. Architecture Decisions
 Have you determined your private/public needs?
 Have you determined on-prem to cloud integration pipelines?
 Have you factored in data and cyber security?
05. Migration Plans
 Have you planned your migration?
 Have you assessed your migration risks?
 Have you aligned with the business?
06. Governance Change
 Have you planned for real-time governance?
 Have you considered master data integration?
 Have you considered data virtualization?
07. Use Case Inventory
 Have you appropriately developed your use case inventory?
 Have you jointly developed use cases with the business units?
 Have you balanced your use cases across value to the organization?
08. Technical Considerations
 Have you documented your technical requirements?
 Have you reviewed local, regional, and legislative considerations?
 Have you evaluated the various technical options?
09. Security Decisions
 Have you assessed and documented your security requirements?
 Have you considered legislative constraints?
 Have you evaluated the various security options?
The Modern Analytics Pre-Flight Checklist

12. Legacy Platform
Initial Investment
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
Figure 1: Yearly Cost Outlay
Modern Analytics
Legacy Analytics
Modern Analytics
Legacy Analytics
Legacy Platform
Initial Investment
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
This is where modern
analytics can cost more
than legacy analytics.
Modern Analytics
Projected Total Cost
Legacy Platform Total
Maintenance Cost
Figure 2: Total Cost Outlay
Modern Analytics
Legacy Analytics
Figure 3: Best Practice Total Cost Outlay
Modern Analytics
Projected Total Cost
Legacy Platform Total
Maintenance Cost
Legacy Platform
Initial Investment
Start small and
focus on AI/ML.
Generate value,
develop your
team, then
migrate
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
Assess Your Technology Cost Outlay
Legacy analytics is expensive up front and then usually decreases over time when paying annual maintenance fees.
Modern analytics can be expensive over time and needs to be managed effectively to ensure healthy cost of ownership.

13. Modern analytics platforms don’t require the typical infrastructure maintenance.
Scripts are needed to bring environments up and down. Environment upgrades are
performed by the vendor, which means infrastructure personnel need to be aware of
and understand the implications of environment changes.
Infrastructure Engineers
Data Engineers
Cloud Architect
Project/Cost Managers
Data Scientists
• Limited opportunity for upskilling; new
talent acquisition recommended
• Focus on scripting skills and automated
environment monitoring
• Acquire new talent
• Contract initially
• Build internal talent
• Upskill where possible
• Contract for best practices
• Acquire new talent
• Contract for best practices
• Use apprentice model
• Upskill where possible
• Leverage coding
• Support with training
Function
Is enhanced by this capability
The traditional ETL (extract, transform, load) data management and transformation
function is now different. The new platform requires extensive use of tools such as
Python. Those with traditional computer science and programming backgrounds are a
better fit.
Architecting cloud solutions is significantly different and better suited to those who
have been immersed in modern technologies and are familiar with big data
architectures and technologies.
Budgeting and managing costs on a modern platform require new skills to optimize
the pay-per-use model. Traditional project management will be limiting, and
practitioners need to learn and operate with Agile methodologies.
Creating solutions leveraging the modern analytics platform while using statistical
modeling requires a combination of math, programming, and domain expertise.
Description Talent Acquisition
Modern Analytics is a Team Sport

14. Modern Analytics = Financial Variability
Legacy Analytics
• Managed by IT
• Utilizes Established Cost Allocation Budgeting
• Capital Expenditure (CAPEX) Allocations
• Slower Response Time
• Low Financial Variability
Modern Analytics
• Managed by Business Units
• Requires New Real-Time Use Budgeting
• Operating Expenditure (OPEX)
• Faster Response Time
• High Financial Variability
Are you ready to handle the
financial variability as you
move from legacy analytics to
modern analytics?

15. User
Private Cloud
Public Cloud
• Private Front-End (Applications)
• Public Back-End (Data)
Private Front-End & Public Back-End
where data is routed through private
data centers with back-end
applications operating in the public
cloud.
01
User
Public Cloud
Private Cloud
• Public Front-End (Applications)
• Private Back-End (Data)
Public Front-End & Private Back-End
where public cloud technologies are
used to interface with the users, but
the data required is stored in a
private, secure cloud.
02
User
Public Cloud
Public Cloud
• Public Front-End and Back-End
(Applications & Data)
• Third-Party Add-on for Cyber
Security
Public Front & Back-End with Third
Party Add-Ons
where the public cloud solution is
integrated with additional
third-party add-ons for cybersecurity
and other requirements.
03
Prepare for Integration Complexity

16. Sunset: With some amount of work, it might be
possible to move the required functionality over into
other applications and use the opportunity to sunset
or retire older applications.
Lift and Shift: The simplest approach, especially
when faced with a time constraint, is to lift and shift
the application to the new environment. However,
this can result in neglecting the opportunity to
improve performance and enhance functionality. It
also means the problems with the legacy system can
be automatically inherited by the modern system.
Lift, Enhance, and Drop: This option involves the
core of an application being migrated as-is, but
also enhanced for performance improvement
and functionality to yield benefits where
applicable and possible.
Reimagine and Rebuild: In some cases, the application
might be outdated, or the new technology or
requirements are significantly different, and it might
be better to start from scratch and reimagine and
rebuild the application in a new way.
Migration Strategy of Critical Importance

17. ETL, APIs, EAI, ESB, etc.
Key data is replicated between legacy
analytics and modern analytics.
Applications and reporting systems
must source the data from each
environment.
Legacy
Analytics
Applications
Reporting &
Analytics
Reporting &
Analytics
Modern
Analytics
Applications Reporting &
Analytics
Reporting &
Analytics
Legacy
Analytics
Modern
Analytics
Virtual System Schema
Reporting &
Analytics
Reporting &
Analytics
Applications
Legacy
Analytics
Accelerated Data Warehouse
Technologies
Modern
Analytics
E.g.: Denodo, Composite, etc.
A single virtual system schema
becomes the primary source for data
needed by the various Applications
and reporting systems across the
organization.
E.g.: Incorta, Kyvos, etc.
Accelerated data warehouse technologies
can be used to deploy data warehouses
focusing on rapid development and
deployment leveraging newer “niche”
technologies.
“Hybrid” Data Mgmt. Strategy Inevitable

18. 70%of use cases should be able to
identify high-value initiatives
that will create change in the
organization
20%of use cases may be mundane,
but can be rapidly delivered
10%of use cases are edge cases
that feature AI, virtual reality
(VR), etc.
When evaluating modern analytics use cases,
we recommend the following:
• Explore small data analytics and obtain a
few quick wins before venturing into big
data analytics
• Ensure the use cases have strong business
ownership where involvement increases
the likelihood of success.
• Focus on use cases where you can
measure results and determine outcomes,
allowing you to drive meaningful change
and realize value derived from project
investment
• Target revenue generation use cases over
cost containment use cases.
Define Use Cases using ‘70/20/10 Model’

19. Regional
It may be important to evaluate where data centers are
located to pay special attention to high availability and
disaster recovery requirements.
01
Location
It may be necessary to ensure compliance with location-
based data residency legislation.
02
Control
It may be necessary to allow your administrators to have a
certain level of control over the management of
infrastructure and environments.
03
Technology
It may play a role in the selection of specific technologies
due to existing constraints (e.g. preferred alignment with
an existing technology vendor or movement toward the
use of open source technologies).
05
Vendor
Effective decision making may rely on evaluating and
understanding the vendor ecosystem and constraints (e.g.
recognizing vendor lock-in risks)
06
Tools
It may be important for administrators to understand what
the tools offer (e.g. environment ramp-up through coding
vs. configuration).
04
The What, Where, and How of Your Tech

20. Public Sector Regulation
Meeting government cloud (e.g.
CJIS, FedRAMP, etc.) needs
Hybrid Environments
Working with public and
private cloud environments
Encryption Keys
Setting up an encryption key
management system
Global Compliance
Ensuring compliance with GDPR
and other regulations
Access
Evaluating identity access
management (IAM) and single
sign-on (SSO)
Encryption Standards
Tracking approved vs. latest
encryption to match needs
Industry Compliance
Ensuring industry compliance
(e.g. HIPAA, ICD-10, PCI)
Audit Compliance
Reviewing the impact and risk
to business operations
Hardware Options
Evaluating hardware keys and
associated logistics
Security Requirements & Considerations

21. 01. Cost & Complexity
 Have you budgeted appropriately?
 Have you planned for additional resources?
 Have you planned for additional vendor management?
02. Hiring & Upskilling
 Have you determined resource and skills needs?
 Have you determined hiring or upskilling needs?
 Have you created a training plan?
03. Budgeting & Procurement
 Have you planned your CAPEX/OPEX shift?
 Have you communicated the change to business units?
 Have you developed an expense allocation plan?
04. Architecture Decisions
 Have you determined your private/public needs?
 Have you determined on-prem to cloud integration pipelines?
 Have you factored in data and cyber security?
05. Migration Plans
 Have you planned your migration?
 Have you assessed your migration risks?
 Have you aligned with the business?
06. Governance Change
 Have you planned for real-time governance?
 Have you considered master data integration?
 Have you considered data virtualization?
07. Use Case Inventory
 Have you appropriately developed your use case inventory?
 Have you jointly developed use cases with the business units?
 Have you balanced your use cases across value to the organization?
08. Technical Considerations
 Have you documented your technical requirements?
 Have you reviewed local, regional, and legislative considerations?
 Have you evaluated the various technical options?
09. Security Decisions
 Have you assessed and documented your security requirements?
 Have you considered legislative constraints?
 Have you evaluated the various security options?
The Modern Analytics Pre-Flight Checklist

22. Thanks For Joining Us
We hope you enjoyed the presentation.
If you’d like to learn more about how to achieve new
heights with modern analytics, download our eBook.
https://sensecorp.com/achieve-new-heights-with-
modern-analytics/
DOWNLOAD EBOOK
www.sensecorp.com | marketing@sensecorp.com

23. Q & A