Edge Database for Telecom Market Outlook

According to our latest research, the global Edge Database for Telecom market size reached USD 2.14 billion in 2024, driven by the escalating need for real-time data processing and network optimization within the telecommunications sector. The market is experiencing robust momentum and is projected to grow at a compound annual growth rate (CAGR) of 18.7% from 2025 to 2033, reaching an estimated USD 10.82 billion by 2033. Key growth factors include the proliferation of 5G networks, the exponential rise in connected devices and IoT applications, and the increasing demand for ultra-low latency services across global telecom infrastructures.

One of the primary growth drivers for the Edge Database for Telecom market is the rapid deployment of 5G technology worldwide. As telecom operators race to upgrade their networks, the need for distributed, high-performance databases at the network edge becomes paramount. Edge databases enable telecom providers to process and analyze vast volumes of data closer to the source, reducing latency and improving the quality of service for end-users. This is particularly crucial for applications such as autonomous vehicles, augmented reality, and mission-critical IoT solutions, where real-time data access and decision-making are essential. Moreover, the increasing adoption of network virtualization and software-defined networking (SDN) further accelerates the integration of edge databases, as these technologies require agile, scalable, and resilient data management solutions.

Another significant growth factor is the surge in data traffic generated by mobile devices, IoT sensors, and smart applications. Telecom operators are under immense pressure to manage, store, and analyze this data efficiently to ensure seamless connectivity and personalized customer experiences. Edge databases provide the necessary infrastructure to cache, process, and analyze data at local edge nodes, reducing the load on central data centers and minimizing backhaul costs. Additionally, the integration of artificial intelligence and machine learning at the edge enables advanced analytics and automation, empowering telecom providers to optimize network performance, detect anomalies, and deliver value-added services to their customers.

Furthermore, the evolving regulatory landscape and growing concerns over data privacy and sovereignty are influencing telecom operators to adopt edge database solutions. By processing and storing sensitive data locally, telecom companies can comply with regional data protection regulations and minimize the risk of data breaches. This localized approach not only enhances security but also improves service reliability, as edge databases can operate independently in the event of network disruptions. The convergence of these factors—technological advancements, regulatory requirements, and customer expectations—continues to propel the Edge Database for Telecom market forward, fostering innovation and competitive differentiation across the industry.

From a regional perspective, North America currently leads the global Edge Database for Telecom market, accounting for the largest revenue share in 2024, followed closely by Asia Pacific and Europe. The presence of major telecom operators, advanced digital infrastructure, and early adoption of edge computing technologies contribute to North America’s dominance. However, Asia Pacific is expected to witness the fastest growth over the forecast period, driven by massive investments in 5G rollouts, expanding mobile subscriber base, and government initiatives to build smart cities and digital economies. Europe, Latin America, and the Middle East & Africa are also witnessing steady adoption, propelled by increasing mobile penetration and strategic collaborations between telecom providers and technology vendors.

Component Analysis

The Edge Database for Telecom market is segmented by component into Software, Hardware, and Services, each playing a vital role in enabling edge data management and analyti

Graph Database for Telecom Networks Market Outlook

According to our latest research, the global graph database for telecom networks market size is valued at USD 1.34 billion in 2024, reflecting a robust adoption rate across the telecom sector. The market is experiencing a strong upward trajectory with a CAGR of 22.7% from 2025 to 2033. By 2033, the market is projected to reach a substantial USD 10.15 billion, driven by the increasing complexity of telecom networks and the urgent need for advanced data management and analytics solutions. The primary growth factor is the surging demand for real-time network analytics and fraud detection capabilities, which are critical for telecom operators seeking operational efficiency and competitive advantage.

The rapid proliferation of connected devices, 5G rollouts, and the exponential growth of data traffic are fundamentally transforming the telecom industry landscape. Telecom networks are evolving into highly complex, dynamic ecosystems that generate vast amounts of interconnected data. Traditional relational databases are often inadequate for handling such intricate relationships and real-time analytics requirements. Graph database solutions are uniquely positioned to address these challenges by enabling telecom operators to model, analyze, and visualize complex network topologies, customer interactions, and transactional data with unparalleled speed and flexibility. This technological shift is a key growth driver, as telecom providers increasingly seek scalable, agile, and intelligent data management platforms to enhance customer experience, optimize network performance, and accelerate digital transformation initiatives.

Another significant growth factor for the graph database for telecom networks market is the escalating threat landscape, particularly in the domain of fraud detection and cybersecurity. Telecom operators are frequent targets of sophisticated fraud schemes, including SIM card cloning, subscription fraud, and network intrusion attempts. Graph databases excel at identifying hidden patterns, relationships, and anomalies within massive datasets, enabling telecom companies to detect and mitigate fraud in real time. The ability to perform advanced analytics on interconnected data sets is empowering telecom operators to proactively safeguard their networks, reduce financial losses, and comply with stringent regulatory requirements. As the complexity of cyber threats intensifies, the adoption of graph database solutions for security and fraud prevention is expected to surge, further fueling market growth.

The growing emphasis on customer-centricity and personalized service delivery is also propelling market expansion. Telecom operators are leveraging graph databases to gain a 360-degree view of customer journeys, preferences, and interactions across multiple touchpoints. This holistic understanding facilitates targeted marketing, churn prediction, and tailored service offerings, which are essential for customer retention and revenue growth in a highly competitive market. The convergence of telecom networks with emerging technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT) is amplifying the need for graph-based analytics, as these technologies rely on real-time, context-aware insights derived from complex data relationships. As a result, the integration of graph databases into telecom network architectures is becoming a strategic imperative for industry leaders.

From a regional perspective, North America currently leads the global graph database for telecom networks market, accounting for the largest revenue share in 2024. The region’s dominance is attributed to the early adoption of advanced analytics technologies, robust digital infrastructure, and the presence of major telecom and technology companies. Asia Pacific is emerging as the fastest-growing region, driven by massive investments in 5G networks, expanding mobile subscriber base, and increasing focus on digital transformation across telecom operators. Europe is also witnessing significant adoption of graph database solutions, particularly in the context of regulatory compliance and network optimization. Meanwhile, Latin America and the Middle East & Africa are gradually catching up, supported by ongoing telecom sector modernization and rising demand for advanced data analytics. The global market outlook remains highly promising, with all regions poised to contribute to sustained growth over the forecast period.<b

The World Telecommunications/ICT Indicators database (WTID) contains time series data for the years 1960, 1965, 1970 and annually from 1975 to 2018 for more than 180 telecommunication/ICT statistics covering fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. Notes including metadata are also included.

The World Telecommunication/ICT Indicators Database contains time series data for the years 1960, 1965, 1970 and annually from 1975 to 2020 for more than 180 telecommunication/ICT statistics covering fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. Data are available for over 200 economies. However, it should be noted that since ITU relies primarily on official economy data, availability of data for the different indicators and years varies. Notes explaining data exceptions are also included. The data are collected from an annual questionnaire sent to official economy contacts, usually the regulatory authority or the ministry in charge of telecommunication and ICT. Additional data are obtained from reports provided by telecommunication ministries, regulators and operators and from ITU staff reports. In some cases, estimates are made by ITU staff; these are noted in the database.

Context

"Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs." [IBM Sample Data Sets]

Content

Each row represents a customer, each column contains customer’s attributes described on the column Metadata.

The data set includes information about:

• Customers who left within the last month – the column is called Churn
• Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies
• Customer account information – how long they’ve been a customer, contract, payment method, paperless billing, monthly charges, and total charges
• Demographic info about customers – gender, age range, and if they have partners and dependents

Inspiration

To explore this type of models and learn more about the subject.

New version from IBM: https://community.ibm.com/community/user/businessanalytics/blogs/steven-macko/2019/07/11/telco-customer-churn-1113

Graph Database for Telecom Networks Market Outlook

According to our latest research, the global market size for Graph Database for Telecom Networks in 2024 stands at USD 1.47 billion, with a robust compound annual growth rate (CAGR) of 22.1% projected from 2025 to 2033. By the end of 2033, the market is expected to reach USD 7.02 billion. This remarkable growth is primarily fueled by the increasing complexity of telecom networks, the proliferation of connected devices, and the urgent need for real-time data processing and analytics to drive operational efficiency and competitive differentiation. As per our latest research, the adoption of graph database technologies is accelerating in the telecom sector, enabling organizations to address challenges related to data interconnectivity, fraud detection, and network optimization.

One of the most significant growth factors in the Graph Database for Telecom Networks market is the exponential rise in data generated by telecom networks, driven by the widespread adoption of 5G technology, IoT devices, and digital transformation initiatives. Telecom operators are increasingly leveraging graph databases to model and manage complex relationships between network elements, subscribers, and services. These databases enable organizations to gain a holistic view of their networks, streamline network management processes, and quickly identify and resolve issues. The ability of graph databases to handle dynamic, highly connected data structures gives telecom operators a strategic advantage in managing network topologies, optimizing routing, and delivering superior customer experiences. As the volume and complexity of telecom data continue to surge, the demand for advanced graph database solutions is expected to grow at a rapid pace, underpinning the market's impressive CAGR.

Another critical driver for the Graph Database for Telecom Networks market is the increasing emphasis on fraud detection and prevention. Telecom networks are frequent targets for sophisticated fraud schemes, including subscription fraud, SIM card cloning, and international revenue share fraud. Traditional relational databases often fall short in detecting complex fraud patterns that span multiple entities and relationships. In contrast, graph databases excel at uncovering hidden connections and suspicious activity in real-time, enabling telecom operators to proactively mitigate risks and reduce financial losses. By integrating graph analytics with machine learning algorithms, telecom companies can enhance their ability to detect anomalies, improve security, and comply with regulatory requirements. This growing need for advanced fraud detection capabilities is a key factor propelling the adoption of graph database technologies in the telecom industry.

The evolution of customer analytics and personalized service offerings is also playing a pivotal role in driving the Graph Database for Telecom Networks market. Telecom operators are increasingly focused on delivering tailored services and experiences to retain customers and increase revenue. Graph databases empower organizations to analyze customer interactions, preferences, and behavior across multiple touchpoints, enabling hyper-personalized marketing, targeted upselling, and improved customer support. The ability to map and analyze complex customer journeys in real-time allows telecom companies to identify high-value segments, predict churn, and design effective retention strategies. As customer expectations continue to rise, the adoption of graph database solutions for advanced analytics and personalized service delivery is expected to accelerate, further fueling market expansion.

Regionally, the Graph Database for Telecom Networks market is witnessing significant growth in Asia Pacific, North America, and Europe, with emerging economies in Latin America and the Middle East & Africa also showing considerable potential. North America currently leads the market, driven by the presence of major telecom operators, advanced network infrastructure, and early adoption of cutting-edge technologies. Asia Pacific is projected to exhibit the highest CAGR during the forecast period, supported by rapid digitalization, expanding mobile subscriber base, and substantial investments in 5G and IoT deployments. Europe remains a key market, benefiting from regulatory initiatives, strong R&D capabilities, and a mature telecom ecosystem. As telecom operators across regions strive to modernize their netw

Edge Database for Telecom Market Outlook

According to our latest research, the global Edge Database for Telecom market size reached USD 1.42 billion in 2024, demonstrating robust adoption across the telecom sector. The market is expected to experience a CAGR of 17.8% from 2025 to 2033, projecting a value of approximately USD 7.12 billion by 2033. This remarkable growth is primarily driven by the surge in data traffic, the proliferation of 5G networks, and the urgent need for real-time data processing at the network edge, which collectively underscore the increasing reliance on edge database solutions within the telecom industry.

One of the most significant growth factors for the edge database for telecom market is the exponential increase in connected devices and Internet of Things (IoT) deployments. Telecom operators are under intense pressure to manage and process massive volumes of data generated from diverse endpoints, including mobile devices, sensors, and smart infrastructure. Edge databases enable telecom providers to process, analyze, and act on data locally, reducing latency and improving the responsiveness of network services. This capability is particularly vital for applications like autonomous vehicles, remote healthcare, and augmented reality, where milliseconds matter. The shift towards decentralized data architectures is fundamentally transforming telecom infrastructure, making edge databases a critical investment for future-ready networks.

Another driving force behind the expansion of the edge database for telecom market is the accelerating rollout of 5G networks worldwide. 5G technology promises ultra-low latency, high bandwidth, and massive device connectivity. However, realizing these benefits requires telecom operators to move data processing closer to the source of data generation. Edge databases provide the backbone for such distributed computing models by supporting real-time analytics, subscriber data management, and network optimization at the edge. As telecom companies race to differentiate their offerings and deliver superior customer experiences, the adoption of edge database solutions is becoming a strategic imperative. This trend is further amplified by the increasing demand for personalized content delivery and network slicing, both of which rely heavily on localized, real-time data processing.

The third major growth factor is the rising focus on network security and regulatory compliance. As data privacy regulations become more stringent and cyber threats more sophisticated, telecom operators are seeking solutions that minimize data exposure and reduce the attack surface. Edge databases facilitate localized data processing and storage, ensuring sensitive information remains within specific geographic boundaries and complies with data sovereignty laws. Moreover, by processing data at the edge, telecom providers can implement advanced security protocols and threat detection mechanisms closer to the source, thereby enhancing overall network security. This trend is particularly pronounced in regions with strict data protection regulations, such as Europe and parts of Asia Pacific, further fueling the adoption of edge database solutions.

From a regional perspective, North America currently leads the edge database for telecom market, followed closely by Asia Pacific and Europe. The dominance of North America is attributed to the early adoption of 5G technology, significant investments in edge computing infrastructure, and the presence of major telecom operators and technology vendors. Asia Pacific, on the other hand, is witnessing the fastest growth, driven by large-scale digital transformation initiatives, rapid urbanization, and the expansion of IoT ecosystems in countries like China, Japan, and South Korea. Europe remains a key market due to its advanced telecom infrastructure and strong regulatory focus on data privacy and security. Latin America and the Middle East & Africa are also emerging as potential growth regions, supported by increasing mobile penetration and ongoing network modernization efforts.

Component Analysis

The edge database for telecom market is segmented by component into software, hardware, and services, each playing a pivotal role in the overall market dynamics. The software segment encompasses database management systems, analytics engines, and security modules that enable telecom operators to efficiently manage and process data at the edge. As the demand for real-time

The World Telecommunication/ICT Indicators database contains time series data for more than 180 telecommunication/ICT (Information and Communication Technologies) statistics. It covers fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. The data is for the years 1960, 1965, 1970 and annually from 1975 to 2017. The WTI Database also includes: Economy yearbook pages featuring in the Yearbook of Statistics. These pages show data in economy tables allowing readers to view the evolution of telecommunication services by economy. Statistics are provided for the ten-year period 2007-2017. The latest (2017) data on ICT access and use by households and individuals. Data are presented in tables and broken down by socio-demographic variables, such as age, sex, income and education level etc. Please note: The World Telecommunication/ICT Indicators database is a relational database which must be used with the associated Software Application. In order to search and extract data from the Data file, users will need to download and install the Application and the Data file to the same folder on their personal computers. The database must be installed by first launching the executable (ending in “.exe”) file.

Connecticut General Statutes §16-50dd requires the Connecticut Siting Council to develop, maintain and update on a quarterly basis a Statewide Telecommunications Coverage Database that includes the location, type and height of all telecommunications towers and antennas in the state. Although the Siting Council has made every effort to ensure that this database is as inclusive as possible, it makes no representation that all telecommunications sites in the state are included in this listing. As the Siting Council becomes aware of sites that are unlisted, it takes steps to add these sites to the listing. The Council also welcomes corrections or additions to this database

The Organisation for Economic Co-operation and Development (OECD) Telecommunications and Internet Statistics covers provides time series of telecommunications and economic indicators such as network dimension, revenues, investment and employment for OECD countries from 1980 onwards. These data allows evaluation of policy performance in this sector across the OECD region.

The OECD Telecommunications and Internet Statistics is made up of the Telecommunications Database and Broadband database.

The Telecommunications Database provides both telecommunication and economic time-series data covering thirty OECD Member countries from 1980 onwards. The broadband database on information and communication technology (ICT) contains indicators on wireless and fixed broadband usage, access and diffusion to OECD households, individuals and businesses.

These data were first provided by the UK Data Service in March 2015.

Customer Contacts Database Information showing customer contacts to UK Contact Centres and One Stop Centres by month. Dataset Guidance:

  F2F = Face-to-face (One Stop Centre) 
  CC = Contact centre (Call centre/telephone) 

Contains customer contact details, support details and support emails. Data collection Published by Intellectual Property Office.

Customer contact data helps support the provision of the corporate data as well as assisting customers with their dealings with IPO. For example contacting customers regarding - acceptance or rejection of services, patents or designs, usage of products and telecommunication services provided by big brands such, Sky, BT, Vodafone, Virginmedia & more.

Discover the booming Big Data in Telecom market! This comprehensive analysis reveals key trends, growth drivers (5G, IoT), major players (Accenture, Amazon, IBM), and regional market share projections (North America, Europe, Asia Pacific) from 2025-2033. Learn how big data is revolutionizing the telecom industry and fueling significant market expansion.

Dataset

This dataset was created by Chetan K

Contents

Dataset

This dataset was created by Qaiser Rizvi

Released under Database: Open Database, Contents: Database Contents

Contents

This dataset represents a selection of 14 indicators, based on questionnaires received by the OECD from relevant national authorities of OECD members and accession countries. Economies, governments and societies across the globe are embracing the digital transformation. In this context, broadband connectivity is an essential tool for accessing communication, information, public services, remote work, online health services and cultural resources. The OECD provides key broadband statistics to help inform policy decisions.

The information presented in this data set is based on records of dockets, petitions, tower share requests, and notices of exempt modifications received and processed by the Council. This database is not an exhaustive listing of all wireless telecommunications sites in the state in that it does not include all information about sites not under the jurisdiction of the Siting Council. The dataset includes a row for each Council action on any given facility. Although the Connecticut Siting Council makes every effort to keep this spreadsheet current and accurate, the Council makes no representation or warranty as to the accuracy of the data presented herein. The public is advised that the records upon which the information in this database is based are kept in the Siting Council’s offices at Ten Franklin Square, New Britain and are open for public inspection during normal working hours from 8:30 a.m. to 4:30 p.m. Monday through Friday. Note to Users: Over the years, some of the wireless companies have had several different corporate identities. In the database, they are identified by the name they had at the time of their application to the Siting Council. To help database users follow the name changes, the list below shows the different names by which the companies have been known. Recent mergers in the telecommunications industry have joined companies listed as separate entities. AT&T Wireless merged with Cingular to do business as New Cingular. Sprint and Nextel have merged to form Sprint/Nextel Corporation. Cingular: SNET, SCLP, and New Cingular after merger with AT&T T-Mobile: Omni (Omnipoint), VoiceStream Verizon: BAM, Cellco AT&T: AT&T Wireless, New Cingular after merger with Cingular, then Cingular rebranded as AT&T Nextel: Smart SMR

This dictionary gathers different disciplines and topics such as: PABX (Private Automatic Branch eXchange), public telephone exchange, switch, microwave radio system, satellites, multiplexer, signalling, printed circuit, telephony, etc.It also contains many synonyms and abbreviations in both languages, as well as meaning, case or applications for polysemic terms.Languages : French - English (GB, US), English (GB, US) - FrenchNumber of entries: 89,200Number of terms per language: about -10% with respect to the number of entries (i.e. ca. 80,000 terms)Disciplines: about 185Format: The database will be delivered as .DBF files, sorted alphabetically in French and English A viewer is also available upon demand. This software enables a spontaneous search French => English and English => French in the database according to different criteria:- by beginning of term, - by included word,- by discipline,- by abbreviation.Viewing format: .FIC (Windev)Please note that the prices indicated here are dependent from the number of entries available which is growing constantly. Please contact us for further details.

This database is created by the Realistic 3D research group at Mid Sweden University, Sundsvall, Sweden. The database details are explained thoroughly in the publication which was published at the 16th International Conference on Quality of Multimedia Experience (QoMEX) in 2024. This database was also reviewed as part of the submission and publication process.

You can use this database in your work under the Creative Commons Attribution 4.0 International (CC-BY 4.0) licence, provided that you cite the database as below:

Zerman, E., Gond, M., Takhtardeshir, S., Olsson, R., & Sjöström, M. (2024). A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications. The 16th International Conference on Quality of Multimedia Experience (QoMEX). IEEE. DOI: 10.1109/QoMEX61742.2024.10598264

BibTeX:

@inproceedings{zerman2024spherical, title = {A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications}, author = {Zerman, Emin and Gond, Manu and Takhtardeshir, Soheib and Olsson, Roger and Sj{"o}str{"o}m, M{\aa}rten}, booktitle = {The 16th International Conference on Quality of Multimedia Experience (QoMEX)}, year = {2024}, organization = {IEEE}, doi = {10.1109/QoMEX61742.2024.10598264}}

This database contains 20 spherical light fields of 1 x 60 views, captured with a consumer-grade 360-degree camera: Insta360 X3. The capture was done using a dolly to ensure the separation between consecutive views is exactly 1 cm. In addition to the original captures, this database also provides outputs for two different use cases: compression and view synthesis. Several parameters, features, and objective quality metric values are also included.

N.B. Only the README file and this description have been updated after the initial submission on 2024-02-09.

This comprehensive dataset delivers 387M+ U.S. phone numbers enriched with deep telecom intelligence and granular geographic metadata, providing one of the most complete national phone data assets available today. Designed for data enrichment, verification, identity resolution, analytics, risk modeling, telecom research, and large-scale customer intelligence, this file combines broad coverage with highly structured attributes and reliable carrier-grade metadata. It is a powerful resource for any organization that needs accurate, up-to-date U.S. phone number data supported by robust telecom identifiers.

Our dataset includes mobile, landline, and VOIP numbers, paired with detailed fields such as carrier, line type, city, state, ZIP code, county, latitude/longitude, time zone, rate center, LATA, and OCN. These attributes make the file suitable for a wide range of applications, from consumer analytics and segmentation to identity graph construction and marketing audience modeling. Updated regularly and validated for completeness, this dataset offers high-confidence coverage across all 50 states, major metros, rural areas, and underserved regions.

Field Coverage & Schema Overview

The dataset contains a rich set of fields commonly required for telecom analysis, identity resolution, and large-scale data cleansing:

Phone Number – Standardized 10-digit U.S. number

Line Type – Wireless, Landline, VOIP, fixed-wireless, etc.

Carrier / Provider – Underlying or current carrier assignment

City & State – Parsed from rate center and location metadata

ZIP Code – Primary ZIP associated with the phone block

County – County name mapped to geographic area

Latitude / Longitude – Approximate geo centroid for the assigned location

Time Zone – Automatically mapped; useful for outbound compliance

Rate Center – Telco rate center tied to number blocks

LATA – Local Access and Transport Area for telecom routing

OCN (Operating Company Number) – Carrier identifier for precision analytics

Additional metadata such as region codes, telecom identifiers, and national routing attributes depending on the number block

These data points provide a complete snapshot of the phone number’s telecom context and geographic footprint.

Key Features

387M+ fully structured U.S. phone numbers

Mobile, landline, and VOIP line types

Accurate carrier and OCN information

Geo-enriched records with city, state, ZIP, county, lat/long

Telecom routing metadata including rate center and LATA

Ideal for large-scale analytics, enrichment, and modeling

Nationwide coverage with consistent formatting and schema

Primary Use Cases 1. Data Enrichment & Appending

Enhance customer databases by adding carrier information, line type, geographic attributes, and telecom routing fields to improve downstream analytics and segmentation.

1. Identity Resolution & Profile Matching

Use carrier, OCN, and geographic fields to strengthen your identity graph, resolve duplicate entities, confirm telephone types, or enrich cross-channel identifiers.

1. Lead Scoring & Consumer Modeling

Build predictive models based on:

Line type (mobile vs landline)

Geography (state, county, ZIP)

Telecom infrastructure and regional carrier assignments Useful for ML/AI scoring, propensity models, risk analysis, and customer lifetime value studies.

1. Compliance-Aware Outreach Planning

Fields like time zone, rate center, and line type support compliant outbound operations, call scheduling, and segmentation of mobile vs landline users for regulated environments.

1. Data Quality, Cleansing & Validation

Normalize customer files, detect outdated or mismatched phone metadata, resolve carrier inconsistencies, and remove non-U.S. or structurally invalid numbers.

1. Telecom Market Analysis

Researchers and telecom analysts can use the dataset to understand national carrier distribution, regional line-type patterns, infrastructure growth, and switching behavior.

1. Fraud Detection & Risk Intelligence

Carrier metadata, OCN patterns, and geographic context support:

Synthetic identity detection

Fraud scoring models

Device/number reputation systems

VOIP risk modeling

1. Location-Based Analytics & Mapping

Lat/long and geographic context fields allow integration into GIS systems, heat-mapping, regional modeling, and ZIP- or county-level segmentation.

1. Customer Acquisition & Audience Building

Build highly targeted audiences for:

Marketing analytics

Look-alike modeling

Cross-channel segmentation

Regional consumer insights

1. Enterprise-Scale ETL & Data Infrastructure

The structured, normalized schema makes this file easy to integrate into:

Data lakes

Snowflake / BigQuery warehouses

ID graphs

Customer 360 platforms

Telecom research systems

Ideal Users

Marketing analytics teams

Data science groups

Identity resolution providers

Fraud & risk intelligence platforms

Telecom analysts

Consumer data platforms

Credit, insurance, and fintech modeling teams

Data brokers & a...

Telecommunications database targeted specifically toward disseminating all valid NPA/NXX combinations in the North American Numbering Plan. It covers all active North American NPA/NXX assignments. Included in the database are NPA (area code), NXX (exchange), country, state, county, latitude, longitude, LATA, time zone, day light saving, population, FIPS, MSA, PMSA, CBSA, ZIP code, Operating Company Number, use type, rate center, COMMON LANGUAGE identifier, and V&H.