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These are the fields available within the RampedUp Global dataset.

CONTACT DATA: Personal Email Address - We manage over 115 million personal email addresses Professional Email - We manage over 200 million professional email addresses Home Address - We manage over 20 million home addresses Mobile Phones - 65 million direct lines to decision makers Social Profiles - Individual Facebook, Twitter, and LinkedIn Local Address - We manage 65M locations for local office mailers, event-based marketing or face-to-face sales calls.

JOB DATA: Job Title - Standardized titles for ease of use and selection Company Name - The Contact's current employer Job Function - The Company Department associated with the job role Title Level - The Level in the Company associated with the job role Job Start Date - Identify people new to their role as a potential buyer

EMPLOYER DATA: Websites - Company Website, Root Domain, or Full Domain Addresses - Standardized Address, City, Region, Postal Code, and Country Phone - E164 phone with country code Social Profiles - LinkedIn, CrunchBase, Facebook, and Twitter

FIRMOGRAPHIC DATA: Industry - 420 classifications for categorizing the company’s main field of business Sector - 20 classifications for categorizing company industries 4 Digit SIC Code - 239 classifications and their definitions 6 Digit NAICS - 452 classifications and their definitions Revenue - Estimated revenue and bands from 1M to over 1B Employee Size - Exact employee count and bands Email Open Scores - Aggregated data at the domain level showing relationships between email opens and corporate domains. IP Address -Company level IP Addresses associated to Domains from a DNS lookup

CONSUMER DATA: Education - Alma Mater, Degree, Graduation Date Skills - Accumulated Skills associated with work experience
Interests - Known interests of contact Connections - Number of social connections. Followers - Number of social followers

Download our data dictionary: https://rampedup.io/our-data

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911 Public Safety Answering Point (PSAP) service area boundaries in New Mexico According to the National Emergency Number Association (NENA), a Public Safety Answering Point (PSAP) is a facility equipped and staffed to receive 9-1-1 calls. The service area is the geographic area within which a 911 call placed using a landline is answered at the associated PSAP. This dataset only includes primary PSAPs. Secondary PSAPs, backup PSAPs, and wireless PSAPs have been excluded from this dataset. Primary PSAPs receive calls directly, whereas secondary PSAPs receive calls that have been transferred by a primary PSAP. Backup PSAPs provide service in cases where another PSAP is inoperable. Most military bases have their own emergency telephone systems. To connect to such system from within a military base it may be necessary to dial a number other than 9 1 1. Due to the sensitive nature of military installations, TGS did not actively research these systems. If civilian authorities in surrounding areas volunteered information about these systems or if adding a military PSAP was necessary to fill a hole in civilian provided data, TGS included it in this dataset. Otherwise military installations are depicted as being covered by one or more adjoining civilian emergency telephone systems. In some cases areas are covered by more than one PSAP boundary. In these cases, any of the applicable PSAPs may take a 911 call. Where a specific call is routed may depend on how busy the applicable PSAPS are (i.e. load balancing), operational status (i.e. redundancy), or time of date / day of week. If an area does not have 911 service, TGS included that area in the dataset along with the address and phone number of their dispatch center. These are areas where someone must dial a 7 or 10 digit number to get emergency services. These records can be identified by a "Y" in the [NON911EMNO] field. This indicates that dialing 911 inside one of these areas does not connect one with emergency services. This dataset was constructed by gathering information about PSAPs from state level officials. In some cases this was geospatial information, in others it was tabular. This information was supplemented with a list of PSAPs from the Federal Communications Commission (FCC). Each PSAP was researched to verify its tabular information. In cases where the source data was not geospatial, each PSAP was researched to determine its service area in terms of existing boundaries (e.g. city and county boundaries). In some cases existing boundaries had to be modified to reflect coverage areas (e.g. "entire county north of Country Road 30"). However, there may be cases where minor deviations from existing boundaries are not reflected in this dataset, such as the case where a particular PSAPs coverage area includes an entire county, and the homes and businesses along a road which is partly in another county. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.

Data set of phone numbers for state-of-the-art businesses, municipalities and county authorities. It is intended to be used together with the data set of the units of public administration. This dataset is part of several data sets about public enterprises. The data sets are referred to as the agency base and were previously on Norge.no. They contain an overview of public enterprises, i.e. government agencies and enterprises’ central, regional and local units, county municipalities and municipalities. Data sets are not updated. The data sets contain information about the name of the enterprise, visiting address, postal address, telephone number, e-mail address, web address (URL), map coordinates (position), coverage (which municipalities the business covers), organisation number, overarching activity, type of organisation, type of affiliation (the way in which an enterprise is linked to the executive government) and quality assessments of the website. Look up on the keyword/tag agency base to see the other datasets. The establishment base is closed and is no longer maintained by the Directorate of Digitalisation (formerly Difi). The datasets were last updated in January 2012. Note that this does not mean that all data was updated in January 2012, but that the last changes were made at that time. Reference to the source When using this dataset, we ask that the source be referred to as follows (cf the NLOD license): The service is based on open data sets from the Directorate of Digitalisation and is subject to the Norwegian License for Public Data (NLOD). The data was last updated in 2012 and is no longer maintained by the Directorate of Digitalisation.

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Thailand Average Monthly Revenue: Per Mobile Phone Number: Prepaid data was reported at 151.000 THB in Sep 2019. This records a decrease from the previous number of 152.000 THB for Jun 2019. Thailand Average Monthly Revenue: Per Mobile Phone Number: Prepaid data is updated quarterly, averaging 152.000 THB from Mar 2014 (Median) to Sep 2019, with 23 observations. The data reached an all-time high of 165.000 THB in Mar 2016 and a record low of 134.000 THB in Sep 2014. Thailand Average Monthly Revenue: Per Mobile Phone Number: Prepaid 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 number of mobile data subscriptions in Latvia was expected to increase to 3.05 million in 2024, with 5G connections accounting for an increased share.

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The total number of mobile data subscriptions in Malawi was forecast to reach ***** million in 2024, with ** connections the most popular.

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 is a collection of layers created by Tian Xie(Intern in DDP) in August, 2018. This collection includes Detroit Parcel Data(Parcel_collector), InfoUSA business data(BIZ_INFOUSA), and building data(Building). The building and business data have been edited by Tian during field research and have attached images.

The total number of mobile data subscriptions in Kosovo was forecast to increase to **** million in 2024, with the majority of connections using ** mobile networks.

Key information about Mexico Teledensity: Mobile

• Mexico Teledensity: Mobile was reported at 100.288 Number in Dec 2022
• This records an increase from the previous number of 99.814 Number for Dec 2021
• Mexico Teledensity: Mobile data is updated yearly, averaging 1.868 Number from Dec 1960 to 2022, with 51 observations
• The data reached an all-time high of 100.288 Number in 2022 and a record low of 0.000 Number in 1987
• Mexico Teledensity: Mobile data remains active status in CEIC and is reported by World Bank
• The data is categorized under World Trend Plus’s Association: Telecommunication Sector – Table MX.World Bank.WDI: Telecommunication

Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.;International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database;Weighted average;Please cite the International Telecommunication Union for third-party use of these data.

Abstract

To facilitate comparisons with the Latin America and the Caribbean (LAC) High-Frequency Surveys collected in 2021, harmonized versions of the COVID-19 High Frequency Phone Surveys 2022 Brazil databases have been produced. The databases follow the same structure as those for the countries in the region (for example, see: COVID-19 LAC High Frequency Phone Surveys 2021 (Wave 1)).

The Brazil 2021 COVID-19 Phone Survey was conducted to provide information on how the pandemic had been affecting Brazilian households in 2021, collecting information along multiple dimensions relevant to the welfare of the population (e.g. changes in employment and income, coping mechanisms, access to health and education services, gender inequalities, and food insecurity). A total of 2,166 phone interviews were conducted across all Brazilian states between July 26 and October 1, 2021. The survey followed an Random Digit Dialing (RDD) sampling methodology using a dual sampling frame of cellphone and landline numbers. The sampling frame was stratified by type of phone and state. Results are nationally representative for households with a landline or at least one cell phone and of individuals of ages 18 years and above who have an active cell phone number or a landline at home.

Geographic coverage

National level.

Analysis unit

Households and individuals of 18 years of age and older.

Sampling procedure

The sample is based on a dual frame of cell phone and landline numbers that was generated through a Random Digit Dialing (RDD) process and consisted of all possible phone numbers under the national phone numbering plan. Numbers were screened through an automated process to identify active numbers and cross-checked with business registries to identify business numbers not eligible for the survey. This method ensures coverage of all landline and cellphone numbers active at the time of the survey. The sampling frame was stratified by type of phone and state. See Sampling Design and Weighting document for more detail.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Available in Portuguese. The questionnaire followed closely the LAC HFPS Questionnaire of Phase II Wave I but had some critical variations.

No of Mobile Phone Subscribers: per 1000 Persons: SB: Tomsk Region data was reported at 1.792 Unit th in 2023. This records an increase from the previous number of 1.784 Unit th for 2022. No of Mobile Phone Subscribers: per 1000 Persons: SB: Tomsk Region data is updated yearly, averaging 1.416 Unit th from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 1.825 Unit th in 2019 and a record low of 0.003 Unit th in 1999. No of Mobile Phone Subscribers: per 1000 Persons: SB: Tomsk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

The Common Core of Data Nonfiscal Survey, 2000-01 (CCD 2000-01) is a data collection that is part of the Common Core of Data (CCD) program; program data is available since 1986-1987 at . CCD-Nonfiscal 2000-01 (https://nces.ed.gov/ccd/index.asp) is a cross-sectional survey that collected non-fiscal data about all public schools, public school districts, and state education agencies in the 50 United States, the District of Columbia, Department of Defense schools, Bureau of Indian Affairs, and other outlying jurisdictions. The data were supplied by state education agency officials and included basic information and descriptive statistics on public elementary and secondary schools and schooling in general. Key information produced from CCD-Nonfiscal 2000-01 include information that described schools and school districts, including name, address, and phone number; student counts by race/ethnicity, grade and sex and full-time equivalent (FTE) staff counts by labor category.

Comprehensive dataset of 3,237 Cell phone stores in State of Rio de Janeiro, Brazil 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.

Brazil Number of Cell Phone User data was reported at 141,644.130 Person th in 2017. This records an increase from the previous number of 138,319.640 Person th for 2016. Brazil Number of Cell Phone User data is updated yearly, averaging 139,981.885 Person th from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 141,644.130 Person th in 2017 and a record low of 138,319.640 Person th in 2016. Brazil Number of Cell Phone User data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Global Database’s Brazil – Table BR.TB010: Number of Cell Phone User: by Sex and Age.

Mexico: Mobile phone subscribers, per 100 people: The latest value from 2022 is 100.29 subscribers per 100 people, an increase from 99.81 subscribers per 100 people in 2021. In comparison, the world average is 118.20 subscribers per 100 people, based on data from 150 countries. Historically, the average for Mexico from 1960 to 2022 is 32.24 subscribers per 100 people. The minimum value, 0 subscribers per 100 people, was reached in 1960 while the maximum of 100.29 subscribers per 100 people was recorded in 2022.

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