You can check the fields description in the documentation: current Full database: https://docs.dataforseo.com/v3/databases/google/full/?bash; Historical Full database: https://docs.dataforseo.com/v3/databases/google/history/full/?bash.

Full Google Database is a combination of the Advanced Google SERP Database and Google Keyword Database.

Google SERP Database offers millions of SERPs collected in 67 regions with most of Google’s advanced SERP features, including featured snippets, knowledge graphs, people also ask sections, top stories, and more.

Google Keyword Database encompasses billions of search terms enriched with related Google Ads data: search volume trends, CPC, competition, and more.

This database is available in JSON format only.

You don’t have to download fresh data dumps in JSON – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

Years are determined by using January 01 (or start date of that year) to January 01

The Geospatial Analytics Market size was valued at USD 98.93 billion in 2023 and is projected to reach USD 227.04 billion by 2032, exhibiting a CAGR of 12.6 % during the forecasts period. The Geospatial Analytics Market describes an application of technologies and approaches processing geographic and spatial data for intelligence and decision-making purposes. This market comprises of mapping tools and software, spatial data and geographic information systems (GIS) used in various fields including urban planning, environmental, transport and defence. Use varies from inventory tracking and control to route optimization and assessment of changes in environment. Other trends are the growth of big data and machine learning to improve the predictive methods, the improved real-time data processing the use of geographic data in combination with other technologies, for example, IoT and cloud. Some of the factors that are fuelling the need to find a marketplace for GIS solutions include; Increasing importance of place-specific information Increasing possibilities for data collection The need to properly manage spatial information in a high stand environment. Recent developments include: In May 2023, Google launched Google Geospatial Creator, a powerful tool that allows users to create immersive AR experiences that are both accurate and visually stunning. It is powered by Photorealistic 3D Tiles and ARCore from Google Maps Platform and can be used with Unity or Adobe Aero. Geospatial Creator provides a 3D view of the world, allowing users to place their digital content in the real world, similar to Google Earth and Google Street View. , In April 2023, Hexagon AB launched the HxGN AgrOn Control Room. It is a mobile app that allows managers and directors of agricultural companies to monitor all field operations in real time. It helps managers identify and address problems quickly, saving time and money. Additionally, the app can help to improve safety by providing managers with a way to monitor the location and status of field workers. , In December 2022, ESRI India announced the availability of Indo ArcGIS offerings on Indian public clouds and services to provide better management, collecting, forecasting, and analyzing location-based data. , In May 2022, Trimble announced the launch of the Trimble R12i GNSS receiver, which has a powerful tilt adjustment feature. It enables land surveyors to concentrate on the task and finish it more quickly and precisely. , In May 2021, Foursquare purchased Unfolded, a US-based provider of location-based services. This US-based firm provides location-based services and goods, including data enrichment analytics and geographic data visualization. With this acquisition, Foursquare aims to provide its users access to various first and third-party data sets and integrate them with the geographical characteristics. , In January 2021, ESRI, a U.S.-based geospatial image analytics solutions provider, introduced the ArcGIS platform. ArcGIS Platform by ESRI operates on a cloud consumption paradigm. App developers generally use this technology to figure out how to include location capabilities in their apps, business operations, and goods. It aids in making geospatial technologies accessible. .

In the most recently reported fiscal year, Google's revenue amounted to 348.16 billion U.S. dollars. Google's revenue is largely made up by advertising revenue, which amounted to 264.59 billion U.S. dollars in 2024. As of October 2024, parent company Alphabet ranked first among worldwide internet companies, with a market capitalization of 2,02 billion U.S. dollars. Google’s revenue Founded in 1998, Google is a multinational internet service corporation headquartered in California, United States. Initially conceptualized as a web search engine based on a PageRank algorithm, Google now offers a multitude of desktop, mobile and online products. Google Search remains the company’s core web-based product along with advertising services, communication and publishing tools, development and statistical tools as well as map-related products. Google is also the producer of the mobile operating system Android, Chrome OS, Google TV as well as desktop and mobile applications such as the internet browser Google Chrome or mobile web applications based on pre-existing Google products. Recently, Google has also been developing selected pieces of hardware which ranges from the Nexus series of mobile devices to smart home devices and driverless cars. Due to its immense scale, Google also offers a crisis response service covering disasters, turmoil and emergencies, as well as an open source missing person finder in times of disaster. Despite the vast scope of Google products, the company still collects the majority of its revenue through online advertising on Google Site and Google network websites. Other revenues are generated via product licensing and most recently, digital content and mobile apps via the Google Play Store, a distribution platform for digital content. As of September 2020, some of the highest-grossing Android apps worldwide included mobile games such as Candy Crush Saga, Pokemon Go, and Coin Master.

Introduction
This field study was conducted in collaboration with Angela Joseph, Enrique Sapena Ventura, and Hasan Hamam. The topic of squirrel abundance was prompted by a shared curiosity about the friendly nature of squirrels that were observed on campus. After some discussion of the environmental factors that may lead to such behaviour, it was decided to investigate the abundance of squirrels found in heavy traffic areas of the York University campus, in comparison to a more natural habitat in a woodlot environment. The remains of food left by humans on the campus, both in garbage cans and on the ground, is believed to play a role in the abundance of squirrels in the urban environment. With more food readily available in the more urban areas of the campus, the squirrels are hypothesized to be more abundant in these areas, as commensalism between the humans and the squirrels should be present. There is no cost to humans, as the garbage being thrown out is waste to us regardless, but the squirrels have a chance of gaining a meal by scavenging the scraps. Predictions If there is commensalism between humans and squirrels, it should be expected that there will be a higher abundance of squirrels located in close proximity to the busiest areas of the campus. This should result in most of the squirrels being near to the central area of the campus, and a much lower number of squirrels in the woodlot. As there is some risk to the squirrels of being in such close contact with humans (we are fairly large omnivores in comparison), the amount of food present should be enough to outweigh the risks, but also be less than the competition of other squirrels feeding elsewhere. This implies that there may be a threshold where the squirrels will have a large enough amount of food to outweigh the risk of coming into too close of a contact with humans, but far enough away to not get trampled or captured. Methods Data was collected from pre-determined areas of the York University, Keele campus. Efforts were made to maintain a consistent size in the areas sampled by comparing size on Google Maps. The Urban environment data was collected along a path beginning at the front of Vari Hall and following Campus Walk around the west end of Steacie Building, ending at the north-east side of Farquharson building just before the greenhouses. The woodlot environment datasets were collected from the woodlot directly south of Chimneystack road on the east end of the campus. A staggered path was followed beginning at the center of the south side and leading through the woodlot to the north end, then looping around the west side to observe the separate copse of trees at the very south west corner. Both the woodlot and urban paths were followed for both datasets and were walked for a total of 45 minutes each time. Data was collected on two consecutive Fridays between 2:30 and 5:30. Weather conditions on the first field day were overcast with light rain, and weather was was warm and sunny on the second field day.

The real-time manufacturing analytics software market is experiencing robust growth, driven by the increasing need for enhanced operational efficiency, improved product quality, and reduced downtime across manufacturing sectors. The market's expansion is fueled by the rising adoption of Industry 4.0 technologies, including the Internet of Things (IoT), cloud computing, and big data analytics. These technologies enable manufacturers to collect and analyze vast amounts of real-time data from various sources, providing valuable insights into production processes, equipment performance, and supply chain dynamics. This allows for proactive decision-making, predictive maintenance, and optimized resource allocation, ultimately leading to significant cost savings and improved competitiveness. We estimate the market size to be approximately $5 billion in 2025, growing at a Compound Annual Growth Rate (CAGR) of 15% through 2033, reaching approximately $15 billion by the end of the forecast period. This growth is expected to be driven by continued adoption across various manufacturing sub-sectors, including automotive, electronics, pharmaceuticals, and food and beverage. Several key trends are shaping the market. The increasing demand for advanced analytics capabilities, such as artificial intelligence (AI) and machine learning (ML), is driving innovation within the software landscape. Furthermore, the shift towards cloud-based solutions offers scalability and accessibility, making real-time analytics more readily available to manufacturers of all sizes. Despite this rapid growth, challenges remain. Data security and integration complexities pose significant hurdles for many companies. The need for skilled personnel to effectively utilize and interpret the insights gleaned from these complex systems also presents an ongoing challenge. Competition amongst established players and emerging startups is intense, leading to continuous innovation and improvement within the software capabilities. The market is further segmented by deployment model (cloud, on-premise), industry vertical, and geographic region, with North America currently holding a significant market share, followed by Europe and Asia-Pacific.

Data are in Excel sheets. Data can be opened and analyzed via open-source software (e.g. R).

description: The location of each site is shown on a Google Map. Data are available as a Google Map with links to Station Information and Data for each site. Data are available for 58 sites along I-75 and for 28 sites along State Road 29 in Big Cypress National Preserve.; abstract: The location of each site is shown on a Google Map. Data are available as a Google Map with links to Station Information and Data for each site. Data are available for 58 sites along I-75 and for 28 sites along State Road 29 in Big Cypress National Preserve.

Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs. However, a gap remains between the computational skills taught in statistics service courses and those required for the use of statistics in scientific research. Ten years after the publication of "Computing in the Statistics Curriculum,'' the nature of statistics continues to change, and computing skills are more necessary than ever for modern scientific researchers. In this paper, we describe research on the design and implementation of a suite of data science workshops for environmental science graduate students, providing students with the skills necessary to retrieve, view, wrangle, visualize, and analyze their data using reproducible tools. These workshops help to bridge the gap between the computing skills necessary for scientific research and the computing skills with which students leave their statistics service courses. Moreover, though targeted to environmental science graduate students, these workshops are open to the larger academic community. As such, they promote the continued learning of the computational tools necessary for working with data, and provide resources for incorporating data science into the classroom.

Methods Surveys from Carpentries style workshops the results of which are presented in the accompanying manuscript.

Pre- and post-workshop surveys for each workshop (Introduction to R, Intermediate R, Data Wrangling in R, Data Visualization in R) were collected via Google Form.

The surveys administered for the fall 2018, spring 2019 academic year are included as pre_workshop_survey and post_workshop_assessment PDF files. 
The raw versions of these data are included in the Excel files ending in survey_raw or assessment_raw.

  The data files whose name includes survey contain raw data from pre-workshop surveys and the data files whose name includes assessment contain raw data from the post-workshop assessment survey.


The annotated RMarkdown files used to clean the pre-workshop surveys and post-workshop assessments are included as workshop_survey_cleaning and workshop_assessment_cleaning, respectively. 
The cleaned pre- and post-workshop survey data are included in the Excel files ending in clean. 
The summaries and visualizations presented in the manuscript are included in the analysis annotated RMarkdown file.

List of herbaria and specimen numbers in respective institutions

The North American Enterprise Information Archiving (EIA) market, valued at $2.71 billion in 2025, is projected to experience robust growth, driven by increasing data volumes, stringent regulatory compliance needs (like HIPAA, GDPR, and CCPA), and the rising adoption of cloud-based solutions. The market's Compound Annual Growth Rate (CAGR) of 11.08% from 2025 to 2033 indicates significant expansion potential. Key growth drivers include the escalating need for robust data security and disaster recovery solutions within organizations, coupled with the increasing demand for efficient eDiscovery processes. The BFSI, IT and Telecom, and Healthcare sectors are major contributors to this growth, owing to their substantial data generation and stringent regulatory compliance requirements. While the cloud deployment model is gaining traction, on-premises solutions continue to hold a significant market share, reflecting concerns around data sovereignty and security among large enterprises. The SME segment presents a substantial untapped market opportunity, with increased awareness of data archiving benefits and the availability of cost-effective solutions expected to fuel growth in this area. Competition among established players like Proofpoint, Commvault, and Microsoft, along with emerging innovative companies, is driving innovation and pricing strategies within the market. The forecast period of 2025-2033 will likely see a shift in market dynamics. We anticipate increased adoption of AI-powered archiving solutions for improved data management and automated processes. The rising popularity of hybrid cloud models, balancing the benefits of cloud and on-premises solutions, is another key trend that will reshape the market landscape. Challenges remain, particularly concerning the high initial investment costs associated with implementing EIA solutions, and the complexity of managing diverse data formats and sources. However, the long-term benefits in terms of compliance, risk mitigation, and improved operational efficiency are expected to outweigh these challenges, contributing to sustained market growth throughout the forecast period. Expansion into untapped markets within North America, particularly within smaller and medium-sized businesses in less digitally mature sectors, presents a significant area of future expansion for vendors. Recent developments include: February 2024 - Veritas, a global leader in secure multicloud data resilience, has entered into a definitive agreement with Cohesity, renowned for its AI-powered data security and management solutions. Under this agreement, Cohesity is set to merge with a segment of Veritas, specifically its data protection business, which will be distinctly separated from the parent company. This strategic alliance promises customers enhanced innovations, bolstered by the combined entity's substantial R&D investments, unwavering dedication to customer success, and access to one of the industry's most extensive partner ecosystems., January 2024, Facebook started archiving all users’ link history on Android and iOS devices, allowing Facebook to utilize the collected data for targeted advertising, which would raise the demand for secured data archiving solutions for the company, supporting the market growth in the future.. Key drivers for this market are: Rising Adoption of Cloud-based and Subscription-based Model, Rapid Increase in the Data Volumes in Enterprises; Integration of Big Data Analytics and AI Technologies. Potential restraints include: Rising Adoption of Cloud-based and Subscription-based Model, Rapid Increase in the Data Volumes in Enterprises; Integration of Big Data Analytics and AI Technologies. Notable trends are: Cloud Segment to Witness Major Growth.

Bitcoin is a crypto currency leveraging blockchain technology to store transactions in a distributed ledger. A blockchain is an ever-growing tree of blocks. Each block contains a number of transactions. To learn more, read the Bitcoin Wiki . This dataset is part of a larger effort to make cryptocurrency data available in BigQuery through the Google Cloud Public Datasets program. The program is hosting several cryptocurrency datasets, with plans to both expand offerings to include additional cryptocurrencies and reduce the latency of updates. You can find these datasets by searching "cryptocurrency" in GCP Marketplace. For analytics interoperability, we designed a unified schema that allows all Bitcoin-like datasets to share queries. To further interoperate with Ethereum and ERC-20 token transactions, we also created some views that abstract the blockchain ledger to be presented as a double-entry accounting ledger. Interested in learning more about how the data from these blockchains were brought into BigQuery? Looking for more ways to analyze the data? Check out our blog post on the Google Cloud Big Data Blog and try the sample query below to get started. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

In 2023, Google's ad revenue amounted to 264.59 billion U.S. dollars. The company generates advertising revenue through its Google Ads platform, which enables advertisers to display ads, product listings and service offerings across Google’s extensive ad network (properties, partner sites, and apps) to web users. Google advertising Advertising accounts for the majority of Google’s revenue, which amounted to a total of 305.63 billion U.S. dollars in 2023. The majority of Google's advertising revenue comes from search advertising. Google market share These revenue figures come as no surprise, as Google accounts for the majority of the online and mobile search market worldwide. As of September 2023, Google was responsible for more than 84 percent of global desktop search traffic. The company holds a market share of more than 80 percent in a wide range of digital markets, having little to no domestic competition in many of them. China, Russia, and to a certain extent, Japan, are some of the few notable exceptions, where local products are more preferred.

This dataset comprises 10,000 user reviews of the BCA Mobile app collected from the Google Play Store between December 24, 2023, and June 12, 2024. Each review includes the user's name, the rating they provided (ranging from 1 to 5 stars), the timestamp of when the review was created, and the text content of the review. The dataset is in Indonesian and focuses on feedback from users in Indonesia. This data can be used to perform sentiment analysis, understand user experiences, identify common issues, and assess the overall performance of the BCA Mobile app during the specified timeframe. The reviews are sorted based on the newest first, providing the latest feedback at the top.

If Artificial Intelligence (AI) still sounds like science fiction to some, it can already be found in all aspects of life. From automatic cash registers to airport security, AI is now slowly taking over the e-commerce business.

This graph represents the ranking of the the perceived beneficial uses of AI in French online retail businesses in 2019. For over 90 percent, the ability for e-marchants to use Artificial Intelligence (AI) would involve the possibility of aggregating a large amount of data (number of page views, previous purchases, etc.) and to make predictive purchase analysis more efficient and in turn, increase the turnover (82 percent). AI would not just be benefitial for consumers, but with Internet solutions moving at a high pace, new technologies come with cyberthreat opportunities. For France, AI could serve as an opportuniy to ensure cybersecurity within companies.

New technologies in e-commerce

Another implication of Artificial Intelligence for e-commerce is the Visual Search, a technology that involves recognizing a product through a picture. This technology is starting to finds it's place on social media selling platforms. Likewise, with the new Voice Search feature through smartphones or indepedent Voice Assistant, AI helps to better understand the customer's spoken phrases in context, interpret them and redeem the right product from the e-merchant. Furthermore, AI would help set up learning mechanims to enlarge the virtuous circle of shopping personalization, even though around 40 percent of the French population expressed being absolutely not interested in virtual personal assistant systems to buy on the internet (e. g. through Google Home, Alexa from Amazon...). In terms of personalization of the online shopping experience, most of French online shoppers expressed their wishes to make the payment process easier and to stay informed about promotions and offers.

AI downfalls and prediction

AI is seeing a rather high level of trust from the consumers' side. Big companies have jumped on the same wagon, supported through a rise in research investments in the past few years. For the year 2023 the predicted AI investments was to attain 1.3 billion euros.

However, the implementation of AI is not self-evident for many businesses, as they state a lack of technological skills to choose and maintain the right AI solution (75 percent). The high cost of this modern applied science was named another downside to it's implementation.

The general feeling is that AI applied to e-commerce would increase the sites' profits while making the client experience better and the client happier. However, in order to achieve personalized experiences companies need to collect their client's data and how much of the French population would be willing to share their information?

People are epxressing their issues with giving away their personal data and are absolutely sure that big players such as Facebook, Amazon or Google are using that data. Some report that even though they have a problem with data collection, they still agree to it in order to gain personal profit from it. For the data introverts, around 20 percent would even renounce being part of the technology developement, even if it meant they had to pay more.

The Mobile Analytics Market size was valued at USD 3,000 million in 2023 and is projected to reach USD 6,200 million by 2032, exhibiting a CAGR of 7.9% during the forecast period. Mobile analytics is the process of collecting and monitoring data for mobile applications to improve the application, its marketing, and user interaction. It employs modern tools such as artificial intelligence and big data to help companies gain a competitive edge and improve their outcomes. It plays a crucial role in decision making, user satisfaction and enhanced monetization hence, playing a crucial role especially in the current mobile environment. Recent developments include: In January 2021, Google announced the launch of Google Analytics 4, a new version of its mobile analytics platform.

In March 2021, Adobe announced the acquisition of Marketo, a leading provider of marketing automation software.

In June 2021, Microsoft announced the launch of Azure Application Insights, a new mobile analytics platform.. Key drivers for this market are: Increasing Adoption of Cloud-based Managed Services to Drive Market Growth. Potential restraints include: Environmental Concerns Associated with Livestock Farming Will Hamper the Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

Long and short term operating systems across top-five operating systems.

According to Cognitive Market Research, the global data analytics outsourcing market size will be USD 22634.8 million in 2025. It will expand at a compound annual growth rate (CAGR) of 36.20% from 2025 to 2033.

North America held the major market share for more than 40% of the global revenue with a market size of USD 8374.88 million in 2025 and will grow at a compound annual growth rate (CAGR) of 34.0% from 2025 to 2033.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 6564.09 million.
APAC held a market share of around 23% of the global revenue with a market size of USD 5432.35 million in 2025 and will grow at a compound annual growth rate (CAGR) of 38.2% from 2025 to 2033.
South America has a market share of more than 5% of the global revenue with a market size of USD 860.12 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.2% from 2025 to 2033.
Middle East had a market share of around 2% of the global revenue and was estimated at a market size of USD 905.39 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.5% from 2025 to 2033.
Africa had a market share of around 1% of the global revenue and was estimated at a market size of USD 497.97 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.9% from 2025 to 2033.
Banking, financial services, & insurance (BFSI) category is the fastest growing segment of the data analytics outsourcing industry

Market Dynamics of Data Analytics Outsourcing Market

Key Drivers for Data Analytics Outsourcing Market

Rising Demand for Customer-Centric Solutions to Boost Market Growth

The growing emphasis on personalized customer experiences is a major driver of the data analytics outsourcing market. Businesses increasingly rely on advanced analytics to understand customer behaviour, preferences, and purchasing patterns. Outsourcing enables access to specialized expertise and tools that help derive actionable insights from complex datasets. These insights allow companies to tailor products, services, and marketing strategies to individual customer needs, enhancing satisfaction and loyalty. As competition intensifies across industries, customer-centricity becomes a key differentiator, driving demand for outsourced analytics services that offer agility, accuracy, and faster time-to-market for customer-driven innovations. In June 2023, Genpact, a global professional services company focused on delivering outcomes that transform businesses, declared it is working with Google Cloud to assist businesses accelerate artificial intelligence (AI) strategies, such as taking advantage of generative AI's adoption to drive actionable business insights.

https://genpact.gcs-web.com/news-releases/news-release-details/genpact-teams-google-cloud-accelerate-artificial-intelligence

Advancement in Technology to Boost Market Growth

Technological advancements are a key driver in the data analytics outsourcing market, enabling faster, more accurate, and scalable analytics solutions. Innovations in artificial intelligence (AI), machine learning (ML), big data platforms, and cloud computing have transformed how data is collected, processed, and interpreted. These technologies allow outsourcing firms to offer sophisticated analytics capabilities at lower costs and with higher efficiency. Real-time analytics, automation of data workflows, and predictive modelling are now more accessible, empowering businesses to gain deeper insights quickly. As a result, companies increasingly outsource to leverage these advanced tools without building in-house infrastructure.

Restraint Factor for the Data Analytics Outsourcing Market

High Cost of Investment Will Limit Market Growth

The high cost of investment in data analytics outsourcing acts as a significant restraint in the market. While outsourcing analytics can offer cost savings in the long run, the initial investment in setting up proper data infrastructure, integrating advanced technologies like AI and machine learning, and maintaining secure cloud platforms can be substantial. Smaller businesses or those with limited budgets may find it challenging to afford such investments. Additionally, the cost of hiring skilled professionals from outsourcing firms with expertise in advanced analytics tools and techniques can also add to the overall financial burden, slowing market adoption.

Market Tren...

Since computers revealed the possibility to collect and evaluate large data, there has been a significant increase in studies measuring the impact of academics. This study aims to analyse International Relations scholars and departments in Turkey by using the data from Google Scholar citation counts. Through this measurement, the study will generate a new ranking list as alternative to existing measurement lists. To control outcomes, Google-generated ranking lists will be compared with data generated from Social Science Citation Index (SSCI). Thus, the study aims to make a data-based contribution to the quality assessment literature, which has become increasingly popular in Turkey. Günümüzde bilgisayarlar geniş verileri toplama ve değerlendirme imkanını ortaya çıkarınca, akademisyenlerin etkisini ölçmeyi hedefleyen çalışmalarda ciddi bir artış oldu. Elinizdeki çalışma da Google Scholar (GS) atıf sayısı verileri üzerinden Türkiye’deki Uluslararası İlişkiler akademisyenlerini ve bölümlerini analiz etmeyi hedeflemektedir. Yapılacak bu analiz ile, mevcut ölçme listelerine alternatif olarak akademisyen ve bölümlerin yeni bir sıralanması ortaya konulmaktadır. GS verilerinden hareketle elde edilen sonuçlar, kontrol amacıyla Social Science Citation Index (SSCI) veri tabanından derlenen makale sayıları ve atıflar ile karşılaştırılmıştır. Böylelikle çalışma Türkiye özelinde gittikçe kapsamlı bir hale gelen nitelik değerlendirme literatürüne verilere dayalı bir katkı yapmayı hedeflemektedir

According to a January 2021 survey of adults worldwide, 66 percent of total respondents agreed on feeling that tech companies hold too much control over their personal data, while only six percent expressed disagreement with the statement. Consumers based in Spain, the United Kingdom, and the United States reported higher levels of concern over data control, with more than seven in ten people feeling that tech companies have too much control over their personal information. While surveyed consumers in Sweden, China, and Indonesia appeared to agree the least with the statement, still more than five in ten reported feeling that tech companies have too much control over their data.

Questionable ethics and security breaches put tech companies under scrutiny

Tech giants, and big tech in particular have been under focus in recent years when it comes to data privacy and consumer-related ethics. While Google has been recipient of not one, but a number of antitrust fines from the EU dating back to 2017, tech giant Yahoo fell victim to various data breaches that resulted in the exposure of 3 billion consumer records in total to date.

User skepticism is growing

No wonder public trust has faltered. The rise of ad-blockers, VPNs and privacy search engines show that consumers are more eager than ever to protect their data online. In the United States, alternative search engine DuckDuckGo saw a surge in popularity from April 2020 - around the start of the COVID-19 pandemic. Meanwhile, over half of those surveyed in the UK said that the public exposure of recent data breaches had impacted their willingness to share personal information. The global pandemic has also hit the tech industry, with companies in the tourism sector taking the biggest blow. Booking.com laid off the highest number of employees during 2020, a total of 4375 members of staff.