Centralizing Data: How Telecom Providers Can Harness Multiple Data Streams

Posted by John Sarkis on Jan 17, 2024 1:31:24 PM

As society's dependence on telecom services intensifies, so does the surge in data volume generated by Communication Service Providers (CSPs)

Telecommunication networks often rely on a mix of backhaul vendors and technologies to ensure seamless connectivity, efficient data transfer, and robust network performance, thereby meeting the increasing demands of users. While this diversity brings benefits, it also introduces complexities in terms of monitoring, management, and issue resolution. 

Adding to the complexity, the data collected by CSP's from these vendors is sometimes scattered across numerous data lakes with various technology and vendor-proprietary formats. This abundance of data provides little benefit unless providers can extract meaningful insights from the diverse network elements embedded in their backend infrastructure.

In this blog post, we'll unravel the impact a centralized data dashboard such as our Event Storage & Analytics Platform can have in reshaping how telecom providers navigate their data operations.

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Topics: Big Data, ESAP, Machine Learning, Fraud Prevention, Data Plumbing

How Telecom Providers Can Detect Anomalies With AI

Posted by John Sarkis on Nov 8, 2023 2:51:47 PM

In the modern hyper-connected world, telecom networks are the backbone of the digital age, keeping us connected in our personal lives and running essential businesses and services. But disruptions like fraud, outages, or dropped calls can cause some serious headaches to both the service provider and their customers.

Traditionally, anomalies within telecom networks were only uncovered at the end of each billing cycle, if detected at all, requiring analysts to comb through seas of data. But now thanks to Machine Learning (ML), we can process and analyze huge stacks of data records to spot trends, detect suspicious outliers, and create connections that humans may have overlooked.

In this blog post, we'll explore how our Event Storage & Analytics Platform (ESAP) puts statistical analysis and machine learning to work for telecom companies, unlocking valuable insights that were previously hidden within their data.

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Topics: Big Data, ESAP, Machine Learning, AI, Artificial Intelligence

Tapping Into AI and Machine Learning to Predict and Prevent Telecom Churn

Posted by John Sarkis on Sep 19, 2023 12:36:54 PM

Predicting customer churn holds a key role in helping telecom companies effectively retain customers. The expense associated with acquiring new customers far outweighs the cost of retaining existing ones. That's why voice providers are diving into AI to identify customers who might be considering switching to another service and take proactive measures.

Amid ongoing shifts in the telecom industry, better-priced deals and packages are driving more people to switch carriers, leaving providers at times feeling powerless as they witness waves of customer departures.

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Topics: ESAP, Machine Learning

New ESAP Features Release Coming in June

Posted by Ryan Guthrie on May 5, 2017 11:51:52 AM

The most common issue we run into when beginning work with a new customer, whether they are a telecom or cable company, is gaining access to data records.  Call detail records (CDRs) and IP detail record (IPDRs) contain an enormous wealth of information that can be used to drive KPIs and analytics for almost any part of the business including operations, marketing, regulatory, revenue assurance, etc.  Unfortunately, we find that that majority of the time these data records are owned by a specific department and gaining access to them can take weeks, months, or in some cases even longer.  As a solutions provider, this can obviously be frustrating.  But when an internal group has the same issues accessing its own data, it can be downright debilitating and ultimately impact customer experience and revenue.

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Topics: Telecom Data Analytics, Big Data, Broadband, ESAP, Cable, Machine Learning