Real-time data analytics for telecommunications

Save millions by improving revenue assurance, optimizing networks, and slashing customer churn

Overview

In the telecommunications business, every consumer and business is a potential consumer. Even so, telecom companies are under pressure like never before to compete in a consolidating market, grow the subscriber base, execute the biggest network build-out ever for 5G, and reduce customer churn

With those challenges, telecom companies have a critical need for faster, more efficient data analytics platforms that can provide insight in-the-moment across all available data, especially new 5G-generated data, without massive new IT investments

Modern 5G analytics with Yellowbrick Data Warehouse

Current options for analyzing vast, complex data like that produced by 5G networks are too limited. Legacy approaches like Teradata and Oracle are inflexible and expensive to buy and scale. Cloud-only options like Snowflake have poor and unpredictable price/performance beyond a few terabytes or tens of users and are unsuitable as edge systems for latency reasons. And data lakes have proven to be useful only as low-cost data stores. Those limitations prevent any significant progress against telecom challenges across OSS/BSS.

Yellowbrick Data Warehouse breaks all those limitations. Based on a redesign/modernization of analytics databases from the ground up to take advantage of highly optimized instances, it offers the best price/ performance for network and application analytics available, along with

Yellowbrick Data Warehouse breaks all those limitations. Based on a redesign/modernization of analytics databases from the ground up to take advantage of highly optimized instances, it offers the best price/ performance for network and application analytics available, along with Learn more at yellowbrick.com 2 operational simplicity and flexibility to support any deployment choice up to—and including—the edge. This unique feature set helps you overcome the hardest telecom industry challenges while unlocking new business opportunities such as IoT analytics like only real-time, interactive access to vast data volumes can.

Yellowbrick’s disruptive technology helps you quickly leave common telecom industry roadblocks behind:

Fast & easy migrations

Yellowbrick is compliant with industry standards for plugging seamlessly into existing environments that include common data integration, BI, and identity management tools. Migrations are fast and easy from any legacy platform, and weʼll work with you to validate your use cases and success metrics along the way.

Next steps

Contact us to explore how Yellowbrick Data Warehouse offers the price/ performance at scale and deployment flexibility that are critical for telecom companies.

Test Drive Yellowbrick Data Warehouse Free for 7 Days
Key facts

$700 billion The economic value to be generated by 5G
GMSA

45% The percent of IoT-generated data that will be stored, processed, and analyzed near or at the edge by 2023
IDC

48 The number of exabytes of global IP traffic that will be created monthly by 2022
Research and Markets

TELECOM CASE STUDY
One of the top 10 mobile operators in the world depends on Yellowbrick to safeguard millions in revenue and increase time-toinsight by 20X.

Previously, the company used a legacy data warehouse on top of a data lake to analyze customer data for use by multiple departments- -for example, to reconcile revenue from prepaid SIM cards sold by retailers. But with an 800% growth in data volume over time, that platform could no longer keep up with business needs.

Results of a painless migration to Yellowbrick Data Warehouse include:

  • Ad hoc queries complete 20X faster, with hundreds of concurrent users accessing six months of transactions for deeper, more accurate insights to support up-sell and cross-sell
  • Operational reports now update in real time, instead of in hours or even days, contributing to more efficient infrastructure utilization 8X more data can be ingested for immediate analysis (up to 1TB per day), enabling analysis of fresher data for use cases like fraud detection
  • Revenue reconciliation now happens in real time instead batch, safeguarding millions in monthly revenue that was at risk