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1. ПОСЛОВНА ТАЈНА/Интерно
Accelerating AI Innovation through Hyperscaler Platforms: Data
Engineering and Data Science Perspective
Conference: Data Science Europe 2024
Metropol Hotel, Belgrade, Serbia, November 21, 2024.
Siniša Arsić, PhD
Telekom Serbia, Strategy and Digital

2. ПОСЛОВНА ТАЈНА/Интерно
Presentation plan
•Prologue
•Core team for implementation of AI models in Telekom Serbia
•Migration of Cloudera data lake to AWS Cloud
•Practical example of using Hyperscaler for implementation of AI models
•New perspective for Data engineer role
•New perspective for Data scientist role
•Key remarks – Biggest challenges and what to look out for

3. ПОСЛОВНА ТАЈНА/Интерно
Prologue
•Telekom Serbia has been implementing full scale products based on AI/ML from 2021.
•In 2024 Telekom Serbia has setup „Methodology for implementation of AI models in the
organization“
•Also in 2024, Telekom Serbia has agreed on management level to define roadmap of AI
use cases to be developed until 2027, as well as Data and analytics modernization
strategy.
•In 2024, efforts to migrate data and analytics stack to cloud were initiated…

4. ПОСЛОВНА ТАЈНА/Интерно
Core team for development of AI models
Members of the core team are defined as follows:
1.Business/product owner
2.Domain experts
3.Project manager
4.Change agent
5.UI/UX designer (process manager)
6.Data and analytics core team
1.Business analyst and Data analysts
2.Data engineers
3.Data scientists and ML engineers

5. ПОСЛОВНА ТАЈНА/Интерно
Migration of Cloudera data lake to AWS Cloud in Telekom Serbia
Project in progress is the migration of Cloudera and Hadoop data lake to AWS Cloud, planned to
end in Q2 2025.
Exploitation of Cloud capabilities can unclock business benefits – from cost improvement to
operational efficiency

6. ПОСЛОВНА ТАЈНА/Интерно
Practical example – AI use case based on huge data source
Data source: Network signalization Anritsu platform
Type of data: Mobile data usage of telco customers, for
web portals and applications
Dataset size: appx 300TB of data for each month
(9 months of historic data)
Expected output: To create a mobile persona profile for
each Telekom Serbia customer, for different CVM campaigns
and sales/customer care activities

7. ПОСЛОВНА ТАЈНА/Интерно
New perspective for Data engineer role
New, involving Cloud
Traditional, On prem
New, involving Cloud

8. ПОСЛОВНА ТАЈНА/Интерно
New perspective for Data scientist role
On premise:
Cloud:

9. ПОСЛОВНА ТАЈНА/Интерно
Key remarks -Biggest challenges and what to look out for
For a data engineer For a data scientist
Data governance ML monitoring and observability in cloud
Access to data
Showcase business impact and business
value
Gaps in tooling Building production grade ML models
Inconsistency of training and
experimentation environments
Skillset for data science in cloud