How businesses can align data initiatives with future goals. For the event: AI, Data, and CRM: Shaping Business through Unique Experiences. For the event: AI, Data, and CRM: Shaping Business through Unique Experiences

1. Bridging the Gap
Aligning Data Initiatives with Business Goals

2. All business are data
businesses
Data makes
business possible
Data is crucial to
businesses of all sizes
Securing data is
mandatory

3. All business need to be
analytic businesses
Without analytics data is a cost center,
not a resource
Businesses need to
“know thyself”
Workers are empowered
with intelligent insights
Augmented intelligence
sees patterns we cannot

4. Data
exponential
growth
4
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While data grows 400%...
…less than 30% gets analyzed!
2025
2020
44 ZB 175 ZB
4X

5. Current
State in
Numbers
of commercial
enterprise apps will
use AI
90%
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Source: International Data Corporation (IDC), Gartner, World Economic Forum, Fortune Business Insights
Global spending on
cognitive and AI systems
$204 B
leading businesses have investments in AI,
but only 14.6% deployed AI in their work
jobs will be eliminated,
and 97 M new created
thanks to AI
85 M
9 out of 10
AI Market
AI skills already exceed the skill level of 80% of people
AI Talent Gap
By 2025
5

6. 6
Researchers
View
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7. Uni Systems Copyright © 2023
Analytics & AI is the #1 investment
for business leaders, however they
struggle to maximize ROI
80%
Users
struggle
report struggling
to become mature
users of data
report data silos &
data management
difficulties as
roadblocks
55%
7

8. Ethical Concerns Misuse
Considerations
8
Security
Intellectual
Property
Biased Errors
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9. Democratizing
Data & AI
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Business alignment
Even the best models are
only useful if they inform
action
AI systems may be vulnerable to
unanticipated attacks
Data &AI Security
Data Governance
Good insights require good data
AI ethics such as transparency and
biases need to be carefully managed
Data &AI
Ethics
Bringing AI into the hands of
more stakeholders bridges the
talent gap
Data & AI Democratization

10. Markets
Horizontal
Solutions
Services
Banking Telecom Public
Private &
Utilities
Solutions
Implementation
Operation
Support
Design
Analysis
Assessment
Consulting
Solution
Portfolio
Vertical Solutions
1
0
Enterprise Applications
Application Infrastructure Solutions
Access & Application Delivery Solutions
Telecom Solutions
Infrastructure Solutions
Cloud
Services
Managed
Services
Data
Analytics
&
AI
Outsourcing
Cybersecurity
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Customer
Experience

11. 11
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Telecom Public
Enterprise Applications
Cloud
Services
Managed
Services
Cybersecurity
Our
Analytics
Practice
DATA SCIENCE
AI, Deep Learning, Machine Learning, Statistical
Modeling, Natural Language Processing, etc.
REPORTING & BI
Visualization, Advanced Analytics, KPIs,
Workflow Automation, etc.
MASTER DATA MANAGEMENT &
GOVERNANCE
Stewardship, Data Quality, Cleansing, etc.
DATA ENGINEERING
Pipelines, ETL, EDW, EDL, ESB, etc.
DATA ACQUISITION
IoT, Social Media, ERP, Legacy Data Stores,
Operational Systems, etc.

12. 12
Microsoft
Fabric

13. 13
Azure AI
Services

14. Customer Analytics
• Customer Segmentation
• Customer Lifetime Value
• Customer Churn
• Personalized
Recommendations
• Predictive Analytics
Conversational AI
• Intelligent Virtual Assistants
• Natural Language Processing
Supply Chain
Optimization
• Demand Forecasting
• Real-Time Price Optimization
• Assortment Optimization
• Store Performance Analytics
Process Automation
• Document Processing
• Employee Onboarding
• Price Optimization
• Complaint Management
Generative AI
• Text Summarization
• Text Classification
• Semantic Search
• Question Answering
Cognitive AI
• Text, Speech, Image Analysis
• Sentiment Analysis
• Entity Recognition
• Contextual Understanding
AIoT
• Predictive Maintenance
• Anomaly Detection
• Smart Metering
Uni Systems AI Offerings
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15. 15
Data
Analytics
Practice
1st company in Greece
1 of few in Europe to achieve the
Analytics on Microsoft Azure
Advanced Specialization
Validating our
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Achievements
Global Achievement
Analytics Advanced Specialization
Deep knowledge Proven success
Extensive experience

16. Organizationa
l Readiness
Business
Cases
Tech
Capabilities
Solution
Design & MVP
• Data & AI Literacy
• Data & AI Talent
• Key Stakeholders
• Governance schema
• Strategy
• Outline key business cases
• Define business value
• Infrastructure
requirements
• Data readiness & quality
• ML Infrastructure
requirements
• Solution design
• Implementation roadmap
• MVP Implementation
• Design →Develop→ Deploy → Repea

17. 17
Οργάνωση και Λειτουργία Συστήματος Διαχείρισης Συνταγών
του ΕΟΠΥΥ
Σύμβαση πλαίσιο για το Ευρωπαϊκό Κέντρο Πρόληψης και
Ελέγχου Νόσων (ECDC) για την παροχή υπηρεσιών ανάπτυξης και
υποστήριξης λειτουργιών πληροφορικής
Ψηφιοποίηση αρχείου υποθηκοφυλακείων για το Εθνικό
Κτηματολόγιο

18. 18
Innovating with Data, 5G and Drones

19. Let’s talk about Data & AI