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Telecom Big Data Analytics, Business Intelligence and Data-Driven Decision Making Training Course

Telecom Big Data Analytics, Business Intelligence and Data-Driven Decision Making Training Course

Advanced | 5 days | Face to Face / Online | Certificate
01

Course Overview

Course Summary
Course Title Telecom Big Data Analytics, Business Intelligence and Data-Driven Decision Making Training Course
Organization Tech For Development (T4D)
Venue Tech For Development (T4D) Training Centre
Duration 5 days
Target Industries
Target Job Roles
Course Fees (Face-to-Face) USD 1,500/KES 99,000 (Exclusive of VAT)
Course Fees (Virtual) USD 1,000/KES 70,000 (Exclusive of VAT)
Training Modes Virtual and face-to-face training
Payment Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course
Accreditation Tech For Development Certificate of Course Completion

Course Overview

This comprehensive 5-day training program is designed to equip telecommunications professionals with advanced knowledge and practical skills required to collect, manage, analyse, visualize, and transform large-scale telecom data into actionable business and operational intelligence. The course addresses the increasing complexity of telecommunications ecosystems, where operators generate massive volumes of structured and unstructured data from networks, subscribers, devices, applications, and digital platforms.

Participants will explore modern telecom data architectures, Big Data technologies, data engineering practices, analytics frameworks, business intelligence platforms, predictive analytics, and real-time decision-support systems. The program covers network analytics, customer intelligence, revenue analytics, operational performance monitoring, and data governance frameworks required for data-driven telecom organizations.

Through practical exercises, industry case studies, and real-world telecom scenarios, participants will develop competencies to harness Big Data analytics for improving network performance, optimizing business operations, enhancing customer experience, and enabling strategic decision-making.

Course Duration

5 Days

Target Participants

  • Telecom Data Analysts
  • Business Intelligence Specialists
  • Network Performance Analysts
  • Data Engineers
  • ICT Managers
  • Digital Transformation Managers
  • Telecom Operations Managers
  • Customer Experience Professionals
  • Marketing and Revenue Management Teams
  • Telecom Regulators and Policy Analysts

Personal Impact

  • Develop advanced understanding of telecom Big Data ecosystems.
  • Enhance skills in analysing complex telecom datasets.
  • Improve ability to develop meaningful dashboards and reports.
  • Strengthen data-driven decision-making capabilities.
  • Gain knowledge of modern analytics tools and technologies.
  • Improve understanding of telecom customer and network intelligence.

Organizational Impact

  • Improved utilization of telecom data assets.
  • Enhanced operational visibility through real-time analytics.
  • Improved network planning and performance management.
  • Better customer retention through analytics-driven insights.
  • Increased efficiency through automated reporting and intelligence systems.
  • Strengthened digital transformation capabilities.

Course Objectives

By the end of this training, participants will be able to:

  • Understand Big Data applications within telecommunications environments.
  • Develop effective telecom data management and analytics strategies.
  • Apply business intelligence techniques for telecom decision-making.
  • Analyse customer, network, and operational data.
  • Develop dashboards and visualization solutions.
  • Implement data governance practices for telecom analytics.
  • Apply predictive analytics for strategic planning and optimization.
02

Course Modules

Course Modules

Module 1: Telecom Big Data Ecosystem and Analytics Transformation

  • Evolution of data-driven telecommunications
  • Role of Big Data in telecom transformation
  • Telecom data sources:
    • Network performance data
    • Customer behaviour data
    • Call Detail Records (CDRs)
    • IoT and connected device data
    • Application and digital service data
  • Challenges of managing telecom data volumes and complexity
  • Opportunities created by advanced analytics
  • Big Data analytics use cases in telecom operators
  • Case Study & Practical Application: Mapping the data ecosystem of a telecom operator and identifying opportunities for analytics-driven improvement.

Module 2: Telecom Data Engineering and Management

  • Telecom data collection and integration
  • Structured, semi-structured, and unstructured data
  • Data pipelines and workflow automation
  • Data lakes and data warehouses
  • Cloud-based telecom analytics platforms
  • Data quality management
  • Metadata management and data governance
  • Case Study & Practical Application: Designing a telecom data architecture to support network and customer analytics.

Module 3: Business Intelligence and Telecom Analytics Platforms

  • Principles of Business Intelligence (BI)
  • Telecom KPI monitoring and reporting
  • Dashboard development concepts
  • Real-time operational intelligence
  • Data visualization principles
  • Automated reporting systems
  • Executive decision-support dashboards
  • Case Study & Practical Application: Developing a telecom performance dashboard integrating network, customer, and operational indicators.

Module 4: Customer Analytics, Revenue Intelligence and Market Insights

  • Customer data analytics frameworks
  • Subscriber behaviour analysis
  • Customer segmentation techniques
  • Churn analysis and retention analytics
  • Revenue forecasting and optimization
  • Digital service adoption analytics
  • Personalization strategies
  • Case Study & Practical Application: Analysing subscriber behaviour data to develop customer retention and revenue growth strategies.

Module 5: Predictive Analytics, Artificial Intelligence and Future Telecom Data Trends

  • Predictive analytics concepts
  • Forecasting telecom demand
  • AI-enabled analytics solutions
  • Prescriptive analytics for decision support
  • Data monetization opportunities
  • Generative AI applications in telecom analytics
  • Future trends:
    • Edge analytics
    • Data fabric architectures
    • Real-time intelligence platforms
    • 6G data ecosystems
  • Case Study & Practical Application: Developing a data analytics strategy for a telecom operator transitioning into an AI-driven organization.
03

Course Administration

Methodology

Instructor-led sessions use a blended learning approach combining presentations, guided practical exercises, web-based tutorials, and group work, delivered by seasoned industry experts. All facilitation and course materials are in English, so participants should be reasonably proficient in the language.

Accreditation

Upon successful completion of this training, participants will be issued a Tech For Development Certificate of Course Completion

Training Venue

The training will be held at the Tech For Development Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.

Accommodation & Airport Transfer

Arranged upon request.For reservations contact the Training Officer:
Email: [email protected]
Phone: (+254) 790 824 179

Tailor-Made

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our T4D Training Centre or at a convenient location.

Payment

Payment should be transferred to the T4D account through a bank on or before the start of the course. Send proof of payment to [email protected].

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2026 Schedules
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Kigali
Addis Ababa
Kuala Lumpur
Accra
Pretoria
Cape Town
Johannesberg
Cairo
Arusha
Machakos
Zanzibar
Kisumu
Nakuru
Mombasa
Nairobi
Naivasha
Kampala
Dubai