The OECD broadband database provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets in the OECD. For further details, please refer to https://www.oecd.org/digital/broadband/broadband-statistics/

Dataset

This dataset was created by Qaiser Rizvi

Released under Database: Open Database, Contents: Database Contents

Contents

The Big Data in Telecom market is experiencing robust growth, driven by the exponential increase in mobile data traffic, the rise of 5G networks, and the increasing need for personalized customer experiences. The market is segmented by application (IoT, Retail, Media, Financial Services, Pharmaceuticals, and Others) and by type of database (Hadoop, NoSQL, MPP Databases, and Others). Key players like Accenture, Amazon, Cisco, IBM, Microsoft, and Oracle are heavily invested in this space, offering a range of solutions from data analytics platforms to cloud-based services. The North American market currently holds a significant share, followed by Europe and Asia Pacific. However, developing regions in Asia Pacific and the Middle East & Africa are exhibiting high growth potential, driven by increasing digital adoption and infrastructure investments. The market's Compound Annual Growth Rate (CAGR) is estimated to be around 15% during the forecast period (2025-2033), indicating substantial future expansion. This growth is fueled by the continuous demand for advanced analytics to optimize network performance, improve customer retention, and develop innovative services such as personalized offers and predictive maintenance. The market faces some restraints, including concerns regarding data security and privacy, as well as the complexities associated with integrating big data solutions into existing telecom infrastructure. Nevertheless, the overall outlook remains optimistic, with the market poised for significant expansion over the next decade. The adoption of advanced technologies such as AI and machine learning further fuels market growth by enabling more sophisticated data analysis and insightful business decisions. The forecast period (2025-2033) suggests a consistent upward trajectory. Several factors contribute to this projection: the continued expansion of 5G coverage globally will generate vast amounts of data requiring sophisticated analytics solutions. Furthermore, the increasing adoption of IoT devices in the telecom sector, coupled with the rise of cloud-based data storage and processing solutions, creates a fertile ground for further market growth. Competition among major players will likely intensify, leading to innovations in pricing models, service offerings, and technological advancements. The integration of big data analytics with other emerging technologies such as blockchain and edge computing will likely shape the future landscape of the market, providing opportunities for both established players and new entrants to contribute to this dynamic space.

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.

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.

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 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.

Growth Rate: Mobile: Total data was reported at 8.070 % in 2017. This records an increase from the previous number of 3.160 % for 2016. Growth Rate: Mobile: Total data is updated yearly, averaging 3.460 % from Dec 2002 (Median) to 2017, with 16 observations. The data reached an all-time high of 10.840 % in 2002 and a record low of 1.240 % in 2014. Growth Rate: Mobile: Total data remains active status in CEIC and is reported by Office of The National Broadcasting and Telecommunications Commission. The data is categorized under Global Database’s Thailand – Table TH.TB006: Telecommunication Statistics: Office of The National Broadcasting and Telecommunications Commission .

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.

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

Context and Methodology

The dataset originates from the research domain of Customer Churn Prediction in the Telecom Industry. It was created as part of the project "Data-Driven Churn Prediction: ML Solutions for the Telecom Industry," completed within the Data Stewardship course (Master programme Data Science, TU Wien).

The primary purpose of this dataset is to support machine learning model development for predicting customer churn based on customer demographics, service usage, and account information.
The dataset enables the training, testing, and evaluation of classification algorithms, allowing researchers and practitioners to explore techniques for customer retention optimization.

The dataset was originally obtained from the IBM Accelerator Catalog and adapted for academic use. It was uploaded to TU Wien’s DBRepo test system and accessed via SQLAlchemy connections to the MariaDB environment.

Technical Details

The dataset has a tabular structure and was initially stored in CSV format. It contains:

• Rows: 7,043 customer records

• Columns: 21 features including customer attributes (gender, senior citizen status, partner status), account information (tenure, contract type, payment method), service usage (internet service, streaming TV, tech support), and the target variable (Churn: Yes/No).

Naming Convention:

• The table in the database is named telco_customer_churn_data.

Software Requirements:

• To open and work with the dataset, any standard database client or programming language supporting MariaDB connections can be used (e.g., Python etc).

• For machine learning applications, libraries such as pandas, scikit-learn, and joblib are typically used.

Additional Resources:

• Source code for data loading, preprocessing, model training, and evaluation is available at the associated GitHub repository: https://github.com/nazerum/fair-ml-customer-churn

Further Details

When reusing the dataset, users should be aware:

• Licensing: The dataset is shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

• Use Case Suitability: The dataset is best suited for classification tasks, particularly binary classification (churn vs. no churn).

• Metadata Standards: Metadata describing the dataset adheres to FAIR principles and is supplemented by CodeMeta and Croissant standards for improved interoperability.

Comprehensive dataset of 18 Telecommunications in New Mexico, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

United States Telecom Rev: TS: Non Telecommunications data was reported at 311.404 USD bn in 2016. This records an increase from the previous number of 301.121 USD bn for 2015. United States Telecom Rev: TS: Non Telecommunications data is updated yearly, averaging 71.493 USD bn from Dec 1992 (Median) to 2016, with 25 observations. The data reached an all-time high of 311.404 USD bn in 2016 and a record low of 6.944 USD bn in 1992. United States Telecom Rev: TS: Non Telecommunications data remains active status in CEIC and is reported by Federal Communications Commission. The data is categorized under Global Database’s USA – Table US.TB001: Telecom Revenue.

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.

Comprehensive dataset of 233 Telecommunications in Germany as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

United States Telecom Rev: TS: Long Distance Private Line data was reported at 13.353 USD bn in 2016. This records an increase from the previous number of 12.778 USD bn for 2015. United States Telecom Rev: TS: Long Distance Private Line data is updated yearly, averaging 12.362 USD bn from Dec 1992 (Median) to 2016, with 25 observations. The data reached an all-time high of 16.402 USD bn in 2001 and a record low of 7.783 USD bn in 1992. United States Telecom Rev: TS: Long Distance Private Line data remains active status in CEIC and is reported by Federal Communications Commission. The data is categorized under Global Database’s USA – Table US.TB001: Telecom Revenue.

Comprehensive dataset of 24 Telecommunications in Connecticut, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

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

Acropolis Telecom Whois Database, discover comprehensive ownership details, registration dates, and more for Acropolis Telecom with Whois Data Center.

Croatia Telecom Services: Number of MMS data was reported at 2,540.475 Unit th in Dec 2020. This records a decrease from the previous number of 2,583.586 Unit th for Sep 2020. Croatia Telecom Services: Number of MMS data is updated quarterly, averaging 4,230.000 Unit th from Mar 2004 (Median) to Dec 2020, with 68 observations. The data reached an all-time high of 20,108.000 Unit th in Sep 2008 and a record low of 0.000 Unit th in Jun 2004. Croatia Telecom Services: Number of MMS data remains active status in CEIC and is reported by Croatian Regulatory Authority for Network Industries. The data is categorized under Global Database’s Croatia – Table HR.TB001: Telecommunication Services.