Big data analytics – Time to up the ante

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Big data analytics could help telcos improve performance, rebuild revenues and regain relevance with consumers, but it is not a quick fix. This report looks at what telcos have done in this area so far and what they need to do next.


Format: PDF filePages: 36 pagesCharts: 05Author: John DevlinPublication Date: October 2017

Table of Contents

  • Executive Summary
  • Big data analytics is important
  • …but it’s not a quick win
  • …it’s a strategic play that takes commitment
  • How is ‘big data analytics’ different from ‘analytics’?
  • Opportunities for telcos: typically internal then external
  • Market development and trends
  • Challenges and restrictions in practice
  • What makes a successful big data strategy?
  • Next steps
  • Introduction
  • Methodology
  • An overview of big data analytics
  • Volume, variety and velocity – plus veracity and value
  • The significance of big data for telcos and their future strategies
  • Market development and trends
  • Challenges and restrictions
  • Optimisation and efficiency versus data monetisation
  • Telcos’ big data ecosystem
  • Case studies and results
  • Early results
  • Big data analytics use cases
  • Examples of internal use-cases
  • Examples of external use cases
  • Findings, conclusions and recommendations

Table of Figure

  • Figure 1: Using Big Data can result in richer data insights
  • Figure 2: The data-centric telco: infusing data to improve efficiency across functions
  • Figure 3: Options for telcos’ big data implementations
  • Figure 4: Telco’s big data partner ecosystem
  • Figure 5: The components of a telco-oriented big data

Technologies and industry terms referenced include: AI (artificial intelligence), big data, big data analytics, case studies, customer service, data privacy, IoT, Machine Learning, operational efficiency, regulation, skills, Use cases, user behaviour