Data Service Analytics

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Rich analytics environment to help your business to gain
more actionable insights

Data Service Analytics

Data has grown exponentially in recent years and harnessing data in practical ways becomes more challenging. To gain actionable insights and realize value from big data, your business needs the right analytics solution.
NTELS Data Service Analytics allows you to aggregate data for users, devices, payment, charging, policy control, and QoS control and leverage your data effectively. Monetize your data using advanced analytics techniques, including multi-dimensional, predictive, real-time and Greenplum/Hadoop analytics.

Data Service Analytics

Features

Objective analysis and prediction of data traffic to improve returns on investments

Objective analysis and prediction of data traffic to improve returns on investments

Improved network performance and user’s QoS

Improved network performance and user’s QoS

Understanding of customers reaction towards changes in pricing plans and policies

Understanding of customers reaction towards changes in pricing plans and policies

Customized pricing plans and policies

Customized pricing plans and policies

Identification of gaps in charging process to minimize leaks in charging

Identification of gaps in charging process to minimize leaks in charging

Contributing to revenue increase through a systematic response to customer complaints

Contributing to revenue increase through a systematic response to customer complaints

Key Functions

  • Revenue improvement by building customer trust in pricing plans and identifying gaps in charging process
  • Quality analysis on access network, device, and application server
  • Predictive model based on trends of data traffic to provide reasonable estimates of traffic considering outliers such as events, days of week, and holidays
  • Network influence analysis by analyzing traffic pattern of applications that affect the network and keepalive messages of SNS and MIM applications (influence factors: attempts, amount of traffic, number of users, and occurrences)
  • Details for user’s data service usage history

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