As of January 2022, the money app Greenlight had the highest number of data segments tracked, collecting 22 different types of data from its users. Launched in 2017, Greenlight is a fintech app for children that allows parents to manage and monitor allowances and spending. Mobile gaming app Pokémon GO was the second most invasive mobile app used by children, collecting 17 different data segments from its users. Only the Amazon Kids+ app and the Kinzoo Social app appeared to collect data over sensitive information from their users.

The number of mobile broadband connections per 100 inhabitants in the United States was forecast to continuously increase between 2024 and 2029 by in total 21.1 connections (+11.49 percent). After the fifteenth consecutive increasing year, the mobile broadband penetration is estimated to reach 204.76 connections and therefore a new peak in 2029. Notably, the number of mobile broadband connections per 100 inhabitants of was continuously increasing over the past years.Mobile broadband connections include cellular connections with a download speed of at least 256 kbit/s (without satellite or fixed-wireless connections). Cellular Internet-of-Things (IoT) or machine-to-machine (M2M) connections are excluded. 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 mobile broadband connections per 100 inhabitants in countries like Canada and Mexico.

As of February 2025, video apps accounted for around 76 percent of global mobile data usage every month. Second-ranked social networking accounted for eight percent of global mobile data volume. The two categories, though, can easily overlap, as users can watch videos via video applications, as well as on social networking applications. Most popular social media platforms with video content Facebook, YouTube, and Instagram were among the most popular social networks in the world, as of October 2021. Each of these platforms allow to post, share, and watch video content on a mobile device. One of the fastest growing global brands, Tiktok, is also a social media platform where users can share video content. In September 2021, the platform reached 1 billion monthly active users. Leading types of mobile video content in the U.S. The United States was the third country in the world based on the number of smartphone users as of May 2021, with around 270 million users. Therefore, mobile content usage in the country was one of the highest in the world, and a big part of it was video content. As of the third quarter of 2021, more than 80 percent of survey respondents in the United States reported watching YouTube on their mobile devices. Social media videos were the second most popular type of content for mobile audiences, with almost six in 10 respondents watching videos on social media platforms like TikTok and Twitter.

When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place" as an answer. 56 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

As of 2023, the average data consumption per user per month in India was at **** gigabytes. 4G data traffic contributes to ** percent of the overall data traffic while 5G was launched in India in October 2022. Increased online education, remote working for professionals and higher OTT viewership contributed to the data traffic growth.

App Download Key StatisticsApp and Game DownloadsiOS App and Game DownloadsGoogle Play App and Game DownloadsGame DownloadsiOS Game DownloadsGoogle Play Game DownloadsApp DownloadsiOS App...

According to the Cognitive Market Research Report, the Data Processing and Hosting Service market size in 2024 was XX Million and is projected to have a compounded annual growth rate of XX% from 2025 to 2033. The emergence of cloud-based platforms and the growing number of small and medium enterprises are driving the market growth of Data Processing and Hosting Services. This market is further segmented by type, application, and deployment. The shared hosting under product type, public website, and public deployment holds the dominant share in the data processing and hosting service. The market is divided into shared hosting, dedicated hosting, collocated hosting, virtual private server hosting, managed hosting, self-managed hosting, and others. The shared hosting sector leads the market since small and medium-sized businesses choose shared servers over other forms of hosting. The Asia-Pacific region is the most dominant due to its high share of the global internet population and major organizations' and SMEs' quick adoption of cloud services The Data Processing and Hosting Services Market is relatively competitive, with significant companies including GoDaddy Operating Company LLC, Bluehost (Endurance International Group), HostGator.com LLC, Hostinger International, Ltd., and Amazon Web Services Inc. Some players presently have a large market share. However, as hosting solutions for professional services progress, new firms are strengthening their market presence, consequently expanding their corporate footprint into emerging markets.

Market Dynamics of Data Processing And Hosting Service Market

Key Drivers of Data Processing And Hosting Service Market

The adoption of web and mobile applications drive the market growth

The boom in web and mobile apps has had a huge impact on the market of data processing and hosting services for backend infrastructure, especially in terms of data processing and data storage. As people use applications more and more for entertainment, shopping, communication, and even healthcare, the number of applications has risen astronomically. Millions of transactions and interactions are handled each day by sites like social networking websites, messaging apps, and online stores. For instance, the demand for virtual health care solutions surged, compelling data hosting providers to expand their infrastructure to support the growing data traffic at a rapid pace.

Web Hosting is gaining traction due to the emergence of cloud-based platforms

Web hosting services are gaining pace in response to increased customer demand for web hosting services that are appropriate for their needs. Furthermore, the increased acceptance of cloud services in organizations is opening up new potential for the web hosting market over time. The rise of the cloud has had a massive impact on data management and hosting services. It is a low-cost way for businesses to make use of current technology and design without incurring the high upfront costs of acquiring, installing, and configuring the necessary hardware, software, and infrastructure. Furthermore, major firms were able to swiftly adapt to a developing data-driven economy by leveraging their current resources and competencies to manage it efficiently. Furthermore, SMBs globally are increasingly demanding cloud-based hosting services, which is likely to boost the web hosting sector throughout the projection period. The move to the cloud makes it easier to create programmes that users can use in their browsers rather than downloading on their devices. This greatly accelerates market expansion. Furthermore, with the introduction of web-based applications, app building became so simple that hosting several apps on a single server became straightforward. For instance, Hostinger International Ltd. is a well-known web hosting firm that offers hosting solutions. Hostinger is a trustworthy web hosting company. They offer fast loading speeds and excellent uptime rates to ensure that users may access the site anytime they want. Hostinger also provides knowledgeable and courteous customer service that is available around the clock. (Source: https://www.hostinger.in/about#:~:text=Hostinger%20is%20one%20of%20the,Hostinger%20and%20hustle%20with%20us) Therefore, the emergence of cloud-based platforms has expanded the data processing and hosting service market.

Growing small a...

This data set contains internet traffic data captured by an Internet Service Provider (ISP) using Mikrotik SDN Controller and packet sniffer tools. The data set includes traffic from over 2000 customers who use Fibre to the Home (FTTH) and Gpon internet connections. The data was collected over a period of several months and contains all traffic in its original format with headers and packets.

The data set contains information on inbound and outbound traffic, including web browsing, email, file transfers, and more. The data set can be used for research in areas such as network security, traffic analysis, and machine learning.

**Data Collection Method: ** The data was captured using Mikrotik SDN Controller and packet sniffer tools. These tools capture traffic data by monitoring network traffic in real-time. The data set contains all traffic data in its original format, including headers and packets.

**Data Set Content: ** The data set is provided in a CSV format and includes the following fields:

1. Timestamp: The date and time the traffic was captured
2. Source IP Address: The IP address of the device that sent the traffic Destination IP Address: The IP address of the device that received the traffic Protocol: The network protocol used for the traffic (e.g. TCP, UDP) Source Port: The port used by the source device for the traffic Destination Port: The port used by the destination device for the traffic Packet Size: The size of the packet in bytes Payload: The payload data of the packet The data set contains a large volume of traffic data from over 2000 customers. The data is organized by timestamp and includes all traffic data in its original format, including headers and packets. The data set contains both inbound and outbound traffic, and covers various types of internet traffic, including web browsing, email, file transfers, and more. one of listed protocols: ipsec-ah - IPsec AH protocol *ipsec-esp - IPsec ESP protocol ddp - datagram delivery protocol egp - exterior gateway protocol ggp - gateway-gateway protocol gre - general routing encapsulation hmp - host monitoring protocol idpr-cmtp - idpr control message transport icmp - internet control message protocol icmpv6 - internet control message protocol v6 igmp - internet group management protocol ipencap - ip encapsulated in ip ipip - ip encapsulation encap - ip encapsulation iso-tp4 - iso transport protocol class 4 ospf - open shortest path first pup - parc universal packet protocol pim - protocol independent multicast rspf - radio shortest path first rdp - reliable datagram protocol st - st datagram mode tcp - transmission control protocol udp - user datagram protocol vmtp - versatile message transport vrrp - virtual router redundancy protocol xns-idp - xerox xns idp xtp - xpress transfer protocol

MAC Protocol Examples 802.2 - 802.2 Frames (0x0004) arp - Address Resolution Protocol (0x0806) homeplug-av - HomePlug AV MME (0x88E1) ip - Internet Protocol version 4 (0x0800) ipv6 - Internet Protocol Version 6 (0x86DD) ipx - Internetwork Packet Exchange (0x8137) lldp - Link Layer Discovery Protocol (0x88CC) loop-protect - Loop Protect Protocol (0x9003) mpls-multicast - MPLS multicast (0x8848) mpls-unicast - MPLS unicast (0x8847) packing-compr - Encapsulated packets with compressed IP packing (0x9001) packing-simple - Encapsulated packets with simple IP packing (0x9000) pppoe - PPPoE Session Stage (0x8864) pppoe-discovery - PPPoE Discovery Stage (0x8863) rarp - Reverse Address Resolution Protocol (0x8035) service-vlan - Provider Bridging (IEEE 802.1ad) & Shortest Path Bridging IEEE 802.1aq (0x88A8) vlan - VLAN-tagged frame (IEEE 802.1Q) and Shortest Path Bridging IEEE 802.1aq with NNI compatibility (0x8100)

**Data Usage: ** The data set can be used for research in areas such as network security, traffic analysis, and machine learning. Researchers can use the data to develop new algorithms for detecting and preventing cyber attacks, analyzing internet traffic patterns, and more.

**Data Availability: ** If you are interested in using this data set for research purposes, please contact us at asfandyar250@gmail.com for more information and references. The data set is available for download on Kaggle and can be accessed by researchers who have obtained permission from the ISP.

We hope this data set will be useful for researchers in the field of network security and traffic analysis. If you have any questions or need further information, please do not hesitate to contact us. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F5985737%2F61c81ce9eb393f8fc7c15540c9819b95%2FData.PNG?generation=1683750473536727&alt=media" alt=""> You can use Wireshark or other software's to view files

GapMaps Mobile Location Data uses location data on mobile phones sourced by Azira which is collected from smartphone apps when the users have given their permission to track their location. It can shed light on consumer visitation patterns (“where from” and “where to”), frequency of visits, profiles of consumers and much more.

Businesses can utilise mobile location data to answer key questions including: - What is the demographic profile of customers visiting my locations? - What is my primary catchment? And where within that catchment do most of my customers travel from to reach my locations? - What points of interest drive customers to my locations (ie. work, shopping, recreation, hotel or education facilities that are in the area) ? - How far do customers travel to visit my locations? - Where are the potential gaps in my store network for new developments?
- What is the sales impact on an existing store if a new store is opened nearby? - Is my marketing strategy targeted to the right audience? - Where are my competitor's customers coming from?

Mobile Location data provides a range of benefits that make it a valuable addition to location intelligence services including: - Real-time - Low-cost at high scale - Accurate - Flexible - Non-proprietary - Empirical

Azira have created robust screening methods to evaluate the quality of mobile location data collected from multiple sources to ensure that their data lake contains only the highest-quality mobile location data.

This includes partnering with trusted location SDK providers that get proper end user consent to track their location when they download an application, can detect device movement/visits and use GPS to determine location co-ordinates.

Data received from partners is put through Azira's data quality algorithm discarding data points that receive a low quality score.

Use cases in Europe will be considered on a case to case basis.

Database of the nation''s substance abuse and mental health research data providing public use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health. The goal is to increase the use of the data to most accurately understand and assess substance abuse and mental health problems and the impact of related treatment systems. The data include the U.S. general and special populations, annual series, and designs that produce nationally representative estimates. Some of the data acquired and archived have never before been publicly distributed. Each collection includes survey instruments (when provided), a bibliography of related literature, and related Web site links. All data may be downloaded free of charge in SPSS, SAS, STATA, and ASCII formats and most studies are available for use with the online data analysis system. This system allows users to conduct analyses ranging from cross-tabulation to regression without downloading data or relying on other software. Another feature, Quick Tables, provides the ability to select variables from drop down menus to produce cross-tabulations and graphs that may be customized and cut and pasted into documents. Documentation files, such as codebooks and questionnaires, can be downloaded and viewed online.

In a survey conducted amongst mobile users in Australia in 2022, around ** percent of respondents indicated that they use their entire mobile internet data allowance each month. Almost one third of respondents indicated that they use most of their data allowance each month. According to the source, the average Australian has around ** gigabytes of data included in their phone plan.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The purpose of this study was to conduct content and process evaluations of current internet safety education (ISE) program materials and their use by law enforcement presenters and schools. The study was divided into four sub-projects. First, a systematic review or "meta-synthesis" was conducted to identify effective elements of prevention identified by the research across different youth problem areas such as drug abuse, sex education, smoking prevention, suicide, youth violence, and school failure. The process resulted in the development of a KEEP (Known Elements of Effective Prevention) Checklist. Second, a content analysis was conducted on four of the most well-developed and long-standing youth internet safety curricula: i-SAFE, iKeepSafe, Netsmartz, and Web Wise Kids. Third, a process evaluation was conducted to better understand how internet safety education programs are being implemented. The process evaluation was conducted via national surveys with three different groups of respondents: Internet Crimes Against Children (ICAC) Task Force commanders (N=43), ICAC Task Force presenters (N=91), and a sample of school professionals (N=139). Finally, researchers developed an internet safety education outcome survey focused on online harassment and digital citizenship. The intention for creating and piloting this survey was to provide the field with a research-based tool that can be used in future evaluation and program monitoring efforts.

Data Broker Service Market Outlook

The global data broker service market size is projected to grow from USD 250 billion in 2023 to an estimated USD 450 billion by 2032, reflecting a compound annual growth rate (CAGR) of 6.7%. This substantial growth can be attributed to increasing digitalization, the exponential rise of data-driven decision-making across industries, and the growing realization of the value derived from data analytics. As businesses continue to recognize the potential of leveraging consumer, business, financial, and health data, the demand for data brokerage services is poised to expand significantly.

One of the primary growth factors for the data broker service market is the increasing importance of data in driving business strategies and operations. Companies are increasingly relying on consumer and market data to gain insights into market trends, consumer behavior, and competitive landscapes. This surge in data utilization across sectors such as retail, healthcare, and finance is propelling the demand for data brokerage services that can provide accurate and comprehensive data sets. The proliferation of digital platforms and the Internet of Things (IoT) has further amplified the volume of data generated, thus boosting the need for efficient data brokerage services.

Moreover, advancements in artificial intelligence (AI) and machine learning (ML) technologies are significantly contributing to the market's growth. These technologies enable enhanced data analysis, predictive analytics, and real-time decision-making, making data brokerage services more valuable. Businesses are increasingly investing in AI and ML to analyze large datasets more efficiently and extract actionable insights. Data brokers, in turn, are leveraging these technologies to offer more sophisticated and tailored data solutions, thus attracting a broader customer base.

Privacy regulations and data protection laws are also playing a crucial role in shaping the data broker service market. While these regulations pose challenges, they also create opportunities for compliant data brokers to differentiate themselves in the market. Companies are more inclined to partner with data brokers that demonstrate robust data governance practices and adhere to regulatory requirements. This trend is driving the market towards more ethical and transparent data brokerage practices, increasing the trust and credibility of data brokers among businesses and consumers alike.

The regional outlook for the data broker service market highlights North America as a dominant player, primarily due to the high adoption of data-driven strategies among businesses and the presence of major data brokerage firms. Europe follows closely, driven by stringent data protection regulations like GDPR, which necessitate secure and compliant data handling. The Asia Pacific region is expected to witness the fastest growth, fueled by the rapid digital transformation in countries like China and India and the increasing use of data analytics in various industries. Latin America and the Middle East & Africa regions are also showing promising growth, supported by the rising awareness of data's strategic value and increasing investments in data analytics infrastructure.

Data Type Analysis

The data broker service market by data type comprises consumer data, business data, financial data, health data, and other categories. Consumer data is one of the most significant segments within this market. This type of data includes information on consumer behavior, preferences, purchasing patterns, and demographics. Businesses leverage consumer data to tailor their marketing strategies, enhance customer experiences, and drive sales growth. The increasing use of digital platforms for shopping, social interaction, and information consumption is continually generating vast amounts of consumer data, thereby fueling the demand for consumer data brokerage services.

Business data, encompassing company profiles, industry trends, and competitive intelligence, is another vital segment. Organizations require business data to strategize market entry, expansion, and competitive positioning. Data brokers play a crucial role in aggregating and providing actionable business insights that help companies navigate complex market dynamics. The rise of global trade, the need for cross-border business intelligence, and the growing importance of data-driven decision-making in corporate strategies are driving the demand for business data brokerage services.

Financial data is crucial for sectors like banking, fina

Beginning March 1, 2022, the "COVID-19 Case Surveillance Public Use Data" will be updated on a monthly basis. This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data. CDC has three COVID-19 case surveillance datasets: COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements) COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements) COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (32 data elements) The following apply to all three datasets: Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf. Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers. Some data cells are suppressed to protect individual privacy. The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the previously updated datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured. Datasets are updated monthly. Datasets are created using CDC’s operational Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy. For more information about data collection and reporting, please see https://wwwn.cdc.gov/nndss/data-collection.html For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html Overview The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020 to clarify the interpretation of antigen detection tests and serologic test results within the case classification. The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported volun

Dataset containing information related to non-NYPD Subjects involved in Force Incidents. The Threat, Resistance, or Injury (TRI) Report is the primary means by which the NYPD records use of force incidents. All reportable instances of force – whether used by a member of the Department, or against the member – are recorded on a TRI Report. Data provided here are a result of the information captured on TRI Reports. Each record corresponds to a non-NYPD subject involved in a force incident. The data can be used to explore the various categories of force incidents and when and in which precinct they occurred. For any given incident, there may be one or more members of service involved. Since NYPD policy requires two-person patrols, most incidents will have at least two members. The data is used to populate the public facing Force Dashboard. (https://app.powerbigov.us/view?r=eyJrIjoiOGNhMjVhYTctMjk3Ny00MTZjLTliNDAtY2M2ZTQ5YWI3N2ViIiwidCI6IjJiOWY1N2ViLTc4ZDEtNDZmYi1iZTgzLWEyYWZkZDdjNjA0MyJ9).

Amazon AWS - Cloud Platforms & Services

Companies using Amazon AWS

We have data on 1,070,574 companies that use Amazon AWS. The companies using Amazon AWS are most often found in United States and in the Computer Software industry. Amazon AWS is most often used by companies with 10-50 employees and 1M-10M dollars in revenue. Our data for Amazon AWS usage goes back as far as 2 years and 1 months.

What is Amazon AWS?

Amazon Web Services (AWS) is a collection of remote computing services, also called web services that make up a cloud computing platform offered by Amazon.com.

Top Industries that use Amazon AWS

Looking at Amazon AWS customers by industry, we find that Computer Software (6%) is the largest segment.

Distribution of companies using Amazon AWS by Industry

 Computer software - 67, 537 companies  Hospitals & Healthcare - 54, 293 companies  Retail - 39, 543 companies  Information Technology and Services - 35, 382 companies  Real Estate - 31, 676 companies  Restaurants - 30, 302 companies  Construction - 29, 207 companies  Automotive - 28, 469 companies  Financial Services - 23, 680 companies  Education Management - 21, 548 companies

Top Countries that use Amazon AWS

49% of Amazon AWS customers are in United States and 7% are in United Kingdom.

Distribution of companies using Amazon AWS by country

 United Sates – 616 2275 companies  United Kingdom – 68 219 companies  Australia – 44 601 companies  Canada – 42 770 companies  Germany – 31 541 companies  India – 30 949 companies  Netherlands – 19 543 companies  Brazil – 17 165 companies  Italy – 14 876 companies  Spain – 14 675 companies

Contact Information of Fields Include:-

• Company Name • Business contact number • Title
• Name • Email Address • Country, State, City, Zip Code • Phone, Mobile and Fax • Website • Industry • SIC & NAICS Code • Employees Size
• Revenue Size
• And more…

Why Buy AWS Users List from DataCaptive?

• More than 1,070,574 companies
• Responsive database • Customizable as per your requirements • Email and Tele-verified list • Team of 100+ market researchers • Authentic data sources

What’s in for you?

Over choosing us, here are a few advantages we authenticate-

• Locate, target, and prospect leads from 170+ countries • Design and execute ABM and multi-channel campaigns • Seamless and smooth pre-and post-sale customer service • Connect with old leads and build a fruitful customer relationship • Analyze the market for product development and sales campaigns • Boost sales and ROI with increased customer acquisition and retention

Our security compliance

We use of globally recognized data laws like –

GDPR, CCPA, ACMA, EDPS, CAN-SPAM and ANTI CAN-SPAM to ensure the privacy and security of our database. We engage certified auditors to validate our security and privacy by providing us with certificates to represent our security compliance.

Our USPs- what makes us your ideal choice?

At DataCaptive™, we strive consistently to improve our services and cater to the needs of businesses around the world while keeping up with industry trends.

• Elaborate data mining from credible sources • 7-tier verification, including manual quality check • Strict adherence to global and local data policies • Guaranteed 95% accuracy or cash-back • Free sample database available on request

Guaranteed benefits of our Amazon AWS users email database!

85% email deliverability and 95% accuracy on other data fields

We understand the importance of data accuracy and employ every avenue to keep our database fresh and updated. We execute a multi-step QC process backed by our Patented AI and Machine learning tools to prevent anomalies in consistency and data precision. This cycle repeats every 45 days. Although maintaining 100% accuracy is quite impractical, since data such as email, physical addresses, and phone numbers are subjected to change, we guarantee 85% email deliverability and 95% accuracy on other data points.

100% replacement in case of hard bounces

Every data point is meticulously verified and then re-verified to ensure you get the best. Data Accuracy is paramount in successfully penetrating a new market or working within a familiar one. We are committed to precision. However, in an unlikely event where hard bounces or inaccuracies exceed the guaranteed percentage, we offer replacement with immediate effect. If need be, we even offer credits and/or refunds for inaccurate contacts.

Other promised benefits

• Contacts are for the perpetual usage • The database comprises consent-based opt-in contacts only • The list is free of duplicate contacts and generic emails • Round-the-clock customer service assistance • 360-degree database solutions

Mobile games make up the majority of video games released each year, with thousands of new additions to the Apple App Store and Google Play Store every year. By the mid-2010s, mobile games had...

Spaceborne Imaging Radar-C (SIR-C) is part of an imaging radar system that was flown on board two Space Shuttle flights (9 - 20 April, 1994 and 30 September - 11 October, 1994). The USGS distributes the C-band (5.8 cm) and L-band (23.5 cm) data. All X-band (3 cm) data is distributed by DLR. There are several types of products that are derived from the SIR-C data: Survey Data is intended as a "quick look" browse for viewing the areas that were imaged by the SIR-C system. The data consists of a strip image of an entire data swath. Resolution is approximately 100 meters, processed to a 50-meter pixel spacing. Files are distributed via File Transfer Protocol (FTP) download. Precision (Standard) Data consists of a frame image of a data segment, which represents a processed subset of the data swath. It contains high-resolution multifrequency and multipolarization data. All precision data is in CEOS format. The following types of precision data products are available: Single-Look Complex (SLC) consists of one single-look file for each scene, per frequency. Each data segment will cover 50 kilometers along the flight track, and is broken into four processing runs (two L band, two C-band). Resolution and polarization will depend on the mode in which the data was collected. Available as calibrated or uncalibrated data. Multi-Look Complex (MLC) is based on an averaging of multiple looks, and consists of one file for each scene per frequency. Each data segment will cover 100 km along the flight track, and is broken into two processing runs (one L band and one C band). Polarization will depend on the modes in which the looks were collected. The data is available in 12.5- or 25-meter pixel spacing. Reformatted Signal Data (RSD) consists of the raw radar signal data only. Each data segment will cover 100 km along the flight track, and the segment will be broken into two processing runs (L-band and C-band). Interferometry Data consists of experimental multitemporal data that covers the same area. Most data takes were collected during repeat passes within the second flight (days 7, 8, 9, and/or 10). In addition, nine data takes were collected during the second flight that were repeat passes of the first flight. Most data takes were also single polarization, although dual and quad polarization data was also collected on some passes. A Digital Elevation Model (DEM) is not included with any of the SIR-C interferometric data. The following types of interferometry products are available: Interferometric Single-Look Complex (iSLC) consists of two or more uncalibrated SLC images that have been processed with the same Doppler centroid to allow interferometric processing. Each frame image covers 50 kilometers along the flight track. The data is available in CEOS format. Raw Interferogram product (RIn) involves the combination of two data takes over the same area to produce an interferogram for each frequency (L-band and C-band). The data is available in TAR format. Reformatted Signal Data (RSD) consists of radar signal data that has been processed from two or more data takes over the same area, but the data has not been combined. Although this is not technically an interferometric product, the RSD can then be used to generate an interferogram. Each frame will cover 100 km along the flight track. The data is available in CEOS format.

The UCSD Network Telescope consists of a globally routed, but lightly utilized /9 and /10 network prefix, that is, 1/256th of the whole IPv4 address space. It contains few legitimate hosts; inbound traffic to non-existent machines - so called Internet Background Radiation (IBR) - is unsolicited and results from a wide range of events, including misconfiguration (e.g. mistyping an IP address), scanning of address space by attackers or malware looking for vulnerable targets, backscatter from randomly spoofed denial-of-service attacks, and the automated spread of malware. CAIDA continously captures this anomalous traffic discarding the legitimate traffic packets destined to the few reachable IP addresses in this prefix. We archive and aggregate these data, and provide this valuable resource to network security researchers. This dataset represents raw traffic traces captured by the Telescope instrumentation and made available in near-real time as one-hour long compressed pcap files. We collect more than 3 TB of uncompressed IBR traffic traces data per day. The most recent 14 days of data are stored locally at CAIDA. Once data slides out of this near-real-time window, the pcap files are off-loaded to a tape storage. This historical Telescope data starting from 2008 are available by additional request.