Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Smart phone price index (CPPI) by North American Product Classification System (NAPCS). The table includes annual data for the most recent reference period and the last four periods. Data are available from January 2015. The base period for the index is (2015=100).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains information on the prices of several mobile phones from different brands. It includes details such as the storage capacity, RAM, screen size, camera specifications, battery capacity, and price of each device.
Columns
• Brand: the manufacturer of the phone
• Model: the name of the phone model
• Storage (GB): the amount of storage space (in gigabytes) available on the phone
• RAM (GB): the amount of RAM (in gigabytes) available on the phone
• Screen Size (inches): the size of the phone's display screen in inches
• Camera (MP): the megapixel count of the phone's rear camera(s)
• Battery Capacity (mAh): the capacity of the phone's battery in milliampere hours
• Price ($): the retail price of the phone in US dollars
Each row represents a different mobile phone model. The data can be used to analyze pricing trends and compare the features and prices of different mobile phones.
** The purpose of creating this dataset is solely for educational use, and any commercial use is strictly prohibited and this dataset was large language models generated and not collected from actual data sources.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
## Overview
Phone Call Usage is a dataset for object detection tasks - it contains Cell Phone annotations for 3,115 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [MIT license](https://creativecommons.org/licenses/MIT).
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Dataset consisting of smartphone sold in Indonesia on November 2022. Specification for each devices was taken from GSMArea. While the prices were taken from various marketplaces (Tokopedia and Shopee) from every brand respective official store. The smartphones listed has to be available to purchase when data is taken.
The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Australia & Oceania and Asia.
https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence
Dataset from Info-communications Media Development Authority. For more information, visit https://data.gov.sg/datasets/d_8bf1863458eefb925c88bda1d2d30ff9/view
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Comparative summary of telephone statistics, by operating details for Canada from 1976 to 1996. (Terminated)
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Related article: Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39.
In this dataset:
We present temporally dynamic population distribution data from the Helsinki Metropolitan Area, Finland, at the level of 250 m by 250 m statistical grid cells. Three hourly population distribution datasets are provided for regular workdays (Mon – Thu), Saturdays and Sundays. The data are based on aggregated mobile phone data collected by the biggest mobile network operator in Finland. Mobile phone data are assigned to statistical grid cells using an advanced dasymetric interpolation method based on ancillary data about land cover, buildings and a time use survey. The data were validated by comparing population register data from Statistics Finland for night-time hours and a daytime workplace registry. The resulting 24-hour population data can be used to reveal the temporal dynamics of the city and examine population variations relevant to for instance spatial accessibility analyses, crisis management and planning.
Please cite this dataset as:
Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39. https://doi.org/10.1038/s41597-021-01113-4
Organization of data
The dataset is packaged into a single Zipfile Helsinki_dynpop_matrix.zip which contains following files:
HMA_Dynamic_population_24H_workdays.csv represents the dynamic population for average workday in the study area.
HMA_Dynamic_population_24H_sat.csv represents the dynamic population for average saturday in the study area.
HMA_Dynamic_population_24H_sun.csv represents the dynamic population for average sunday in the study area.
target_zones_grid250m_EPSG3067.geojson represents the statistical grid in ETRS89/ETRS-TM35FIN projection that can be used to visualize the data on a map using e.g. QGIS.
Column names
YKR_ID : a unique identifier for each statistical grid cell (n=13,231). The identifier is compatible with the statistical YKR grid cell data by Statistics Finland and Finnish Environment Institute.
H0, H1 ... H23 : Each field represents the proportional distribution of the total population in the study area between grid cells during a one-hour period. In total, 24 fields are formatted as “Hx”, where x stands for the hour of the day (values ranging from 0-23). For example, H0 stands for the first hour of the day: 00:00 - 00:59. The sum of all cell values for each field equals to 100 (i.e. 100% of total population for each one-hour period)
In order to visualize the data on a map, the result tables can be joined with the target_zones_grid250m_EPSG3067.geojson data. The data can be joined by using the field YKR_ID as a common key between the datasets.
License Creative Commons Attribution 4.0 International.
Related datasets
Järv, Olle; Tenkanen, Henrikki & Toivonen, Tuuli. (2017). Multi-temporal function-based dasymetric interpolation tool for mobile phone data. Zenodo. https://doi.org/10.5281/zenodo.252612
Tenkanen, Henrikki, & Toivonen, Tuuli. (2019). Helsinki Region Travel Time Matrix [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3247564
The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Mexico and Canada.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset contains information on Samsung mobile sales, 5G network adoption, and market factors. It includes details such as regional 5G coverage, subscriber growth, and marketing influence.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset contains detailed specifications and official launch prices of various mobile phone models from different companies. It provides insights into smartphone hardware, pricing trends, and brand competitiveness across multiple countries. The dataset includes key features such as RAM, camera specifications, battery capacity, processor details, and screen size.
One important aspect of this dataset is the pricing information. The recorded prices represent the official launch prices of the mobile phones at the time they were first introduced in the market. Prices vary based on the country and the launch period, meaning older models reflect their original launch prices, while newer models include their most recent launch prices. This makes the dataset valuable for studying price trends over time and comparing smartphone affordability across different regions.
Features:
English(the United States) Scripted Monologue Smartphone speech dataset_Guiding, collected from monologue based on given prompts, covering smart car, smart home, voice assistant domains. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(344 speakers), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.
Percentage of smartphone users by selected smartphone use habits in a typical day.
Homeland Infrastructure Foundation-Level Data (HIFLD) geospatial data sets containing information on Mobile Home Parks.
Global Telemarketing Data | 95% Phone & Email Accuracy | 270M+ Verified Contacts Forager.ai redefines telemarketing success with the world’s most actionable contact database. We combine 100M+ mobile numbers and 170M+ verified emails with deep company insights – all updated every 14 days to maintain 95% accuracy rates that outperform legacy providers.
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Direct mobile numbers
Verified corporate emails
Department hierarchy mapping
Purchase intent signals
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Your Complete Telemarketing Toolkit Core Data Points: ✔ Direct dial mobile/work numbers ✔ Verified corporate email addresses ✔ Job title & decision-making authority ✔ Company size/revenue/tech stack ✔ Department structure & team size ✔ Location data (HQ/local offices) ✔ LinkedIn/Social media validation
Proven Use Cases • Cold Calling 2.0: Target CROs with mobile numbers + know their tech stack before dialing • Email-to-Call Sequencing: Match verified emails to mobile numbers for 360° outreach • List Hygiene: Clean existing CRM contacts against our live database • Market Expansion: Target specific employee counts (50-200 person companies) • Event Follow-Ups: Re-engage webinar/trade show leads with updated contact info
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Real-Time API: Connect to Five9/Aircall/Salesforce
CRM-Ready Files: CSV with custom fields
Compliance Hub: Automated opt-out tracking
PostgreSQL Sync/ JSON files: 2-3 weeks updates for large datasets
Why We Outperform Competitors → 62% Connect Rate: Actual client result vs. industry 38% average → 3:1 ROI Guarantee: We’ll prove value or extend your license → Free Audit: Upload 10K contacts – we’ll show % salvageable
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Telemarketing Data | Verified Contact Database | Cold Calling Lists | Phone & Email Data | Decision-Maker Contacts | CRM Enrichment | GDPR-Compliant Leads | B2B Contact Data | Sales Prospecting | ABM Targeting
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset provides temporary migration estimates at the (origin*destination*time)-level in Senegal derived from mobile phone data for the period 2013-2015. Origin and destination locations are comprised of 39 cities and 112 rural areas of third-level administrative units (i.e., districts), defining the spatial resolution of the dataset. Estimates are provided for each half-month period, defining the temporal resolution of the dataset.
The dataset "tin00083" has been discontinued since 13/07/2023.
Success.ai’s Phone Number Data offers direct access to over 50 million verified phone numbers for professionals worldwide, extracted from our expansive collection of 170 million profiles. This robust dataset includes work emails and key decision-maker profiles, making it an essential resource for companies aiming to enhance their communication strategies and outreach efficiency. Whether you're launching targeted marketing campaigns, setting up sales calls, or conducting market research, our phone number data ensures you're connected to the right professionals at the right time.
Why Choose Success.ai’s Phone Number Data?
Direct Communication: Reach out directly to professionals with verified phone numbers and work emails, ensuring your message gets to the right person without delay. Global Coverage: Our data spans across continents, providing phone numbers for professionals in North America, Europe, APAC, and emerging markets. Continuously Updated: We regularly refresh our dataset to maintain accuracy and relevance, reflecting changes like promotions, company moves, or industry shifts. Comprehensive Data Points:
Verified Phone Numbers: Direct lines and mobile numbers of professionals across various industries. Work Emails: Reliable email addresses to complement phone communications. Professional Profiles: Decision-makers’ profiles including job titles, company details, and industry information. Flexible Delivery and Integration: Success.ai offers this dataset in various formats suitable for seamless integration into your CRM or sales platform. Whether you prefer API access for real-time data retrieval or static files for periodic updates, we tailor the delivery to meet your operational needs.
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Information Technology Usage and Penetration - Table 720-90006 : Persons aged 10 and over who had a mobile phone (including smartphone) by sex and age group
In 2022, the average data used per smartphone per month worldwide amounted to ** gigabytes (GB). The source forecasts that this will increase almost four times reaching ** GB per smartphone per month globally in 2028.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Smart phone price index (CPPI) by North American Product Classification System (NAPCS). The table includes annual data for the most recent reference period and the last four periods. Data are available from January 2015. The base period for the index is (2015=100).