Overview
Communications service providers (CSP) are under pressure to cut costs and boost average revenue per user (ARPU), while maintaining a top-notch customer experience, but data volumes continue to rise. Global mobile data traffic is projected to grow at an annual compound growth rate of 78 percent by 2016, reaching 10.8 exabytes monthly.
Simultaneously, CSPs are generating vast amounts of data, including call detail records (CDR), network information, and customer details. Companies that fully leverage this data gain a competitive advantage. A recent survey by The Economist Intelligence Unit found that companies using data-driven decision-making experience a 5-6% productivity boost. However, only half of the valuable data is utilized by 53% of businesses, with one-fourth noting that significant amounts of useful data are overlooked. The sheer volume of data makes manual analysis impractical and most legacy software systems struggle to keep up, leading to valuable data being discarded or ignored.
With Big Data & Analytics’ high-speed, scalable big data software, CSPs can analyze all their data for improved decision-making in less time. Various Big Data products and techniques offer an end-to-end platform for collecting, preparing, analyzing, and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn prevention, and credit risk analysis. These Big Data & Analytics solutions can handle terabytes of data, but implementing such tools requires a new type of cloud-based database system like Hadoop or massive-scale parallel computing processors (KPU, etc.).
This course on Big Data BI for Telco covers all the emerging areas where CSPs are investing to enhance productivity and open up new revenue streams. It provides a comprehensive 360-degree overview of Big Data BI in the telecommunications sector so that decision-makers and managers can gain a broad understanding of the potential benefits of Big Data BI for productivity and revenue growth.
Course Objectives
The primary goal of this course is to introduce new Big Data business intelligence techniques across four sectors of Telecom Business (Marketing/Sales, Network Operations, Financial Operations, and Customer Relationship Management). Students will be introduced to the following:
- An introduction to Big Data, including the 4Vs (volume, velocity, variety, veracity) from a Telco perspective
- The differences between Big Data analytics and legacy data analytics
- Justifying the use of Big Data within a Telco context
- Familiarity with the Hadoop ecosystem and its tools like Hive, Pig, SPARC – understanding when and how they are used to address Big Data challenges
- The process of extracting data for analysis using an integrated Hadoop dashboard approach to ease business analysts' pain points in collecting and analyzing data
- Basic insights into analytics, visualization, and predictive analytics specific to Telco
- Customer churn analytics and how Big Data can reduce customer churn and dissatisfaction – case studies included
- Analyzing network failures and service issues using Network metadata and IPDR
- Financial analysis for fraud detection, waste reduction, and ROI estimation from sales and operational data
- Solving customer acquisition challenges through targeted marketing, customer segmentation, and cross-selling based on sales data
- A summary of all Big Data analytic products and their roles in the Telco analytics landscape
- Steps to introduce Big Data Business Intelligence into your organization
Target Audience
- Network Operations, Financial Managers, CRM managers, and top IT managers within the Telco CIO office.
- Telco business analysts
- CFO office managers/analysts
- Operational managers
- QA managers
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