The global proxy network software market is experiencing robust growth, driven by increasing demand for data privacy, web scraping, and enhanced online security across various sectors. The market, estimated at $5 billion in 2025, is projected to exhibit a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This expansion is fueled by the proliferation of large enterprises and SMEs adopting proxy solutions for improved data collection, market research, competitive intelligence, and enhanced website security. Significant trends include the rising adoption of residential proxies for bypassing geo-restrictions and enhanced anonymity, the increasing sophistication of datacenter proxies for high-volume tasks, and a growing preference for software solutions that offer better management and scalability. However, market growth faces certain restraints, including regulatory hurdles surrounding data scraping, concerns about ethical implications, and the ongoing battle against proxy detection and blocking techniques employed by websites. The segmentation reveals a considerable market share held by large enterprises leveraging proxy networks for complex business operations, alongside a rapidly expanding SME sector embracing these technologies for cost-effective solutions. Geographically, North America and Europe currently dominate the market, but the Asia-Pacific region is expected to demonstrate significant growth potential in the coming years, driven by burgeoning technological advancements and increased internet penetration. The competitive landscape is highly dynamic, with a mix of established players like Bright Data and Oxylabs alongside emerging competitors. This competition fosters innovation and continuous improvement in proxy network software, including the development of more sophisticated features like advanced security protocols, automated management tools, and improved speed and reliability. The market is characterized by ongoing consolidation and strategic partnerships, as companies strive to enhance their product offerings and expand their market reach. The future of the proxy network software market will depend on the evolution of technology, regulatory environments, and the ever-changing needs of users across various sectors. Continuous innovation and adaptation to evolving threats and opportunities will be vital for sustained success in this rapidly evolving landscape.

The residential proxy IP network market is experiencing robust growth, driven by increasing demand for data scraping, web automation, and online privacy solutions. Businesses across various sectors, including market research, e-commerce, and social media monitoring, rely on residential proxies to circumvent geo-restrictions, enhance data collection accuracy, and avoid IP blocking. The market's expansion is fueled by the rise of big data analytics, the growing need for real-time insights, and the increasing sophistication of anti-scraping technologies. While challenges exist, such as regulatory scrutiny regarding data privacy and the ethical considerations surrounding web scraping, the overall market outlook remains positive. Assuming a conservative CAGR of 15% (a common growth rate for technology sectors experiencing high demand) and a 2025 market size of $1.5 billion, the market is projected to reach approximately $3.5 billion by 2033. This growth is underpinned by the continuous development of more sophisticated proxy technologies and the expanding user base across different market segments like large enterprises and SMEs who are increasingly recognizing the value proposition of residential proxies. The segmentation of the market into services, software, and applications tailored for large enterprises and SMEs reflects the varied needs and technological capabilities of different user groups. Geographically, North America and Europe currently hold significant market shares due to higher adoption rates and established technological infrastructure. However, growth in Asia-Pacific and other emerging regions is expected to accelerate as internet penetration and digitalization increase. Competition is intense, with numerous providers vying for market share through technological innovation, pricing strategies, and the development of robust and reliable infrastructure. The market continues to evolve, with a clear emphasis on providing enhanced security, anonymity, and performance to address the increasing demands of a sophisticated user base.

The Residential Proxy IP Network market is experiencing robust growth, projected to reach $118.1 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 3.8% from 2025 to 2033. This expansion is fueled by the increasing demand for data privacy and anonymity across various sectors. Businesses are leveraging residential proxies for web scraping, market research, brand protection, and social media monitoring, driving market growth. Furthermore, the rise of sophisticated anti-bot technologies necessitates the use of residential proxies to circumvent these measures and access crucial online data. The market segmentation reveals a strong presence of both services and software solutions catering to large enterprises and SMEs, indicating a broad application across different organizational scales. North America and Europe currently hold significant market shares, driven by a higher adoption rate of technology and a robust digital infrastructure; however, the Asia-Pacific region is poised for significant growth due to the increasing digitalization and the expanding e-commerce sector. The competitive landscape is characterized by a mix of established players and emerging companies, leading to ongoing innovation and product differentiation within the market. The continued growth of e-commerce, the rise of big data analytics, and the increasing focus on online security all contribute to a positive outlook for the residential proxy market. While challenges like regulatory changes and concerns over ethical implications of data scraping exist, the overall demand for reliable and secure access to online data continues to outpace these concerns. The market is expected to witness further consolidation as larger players acquire smaller companies, leading to improved technology and broader service offerings. Specific segments such as those providing specialized services for specific regions or industries are showing particularly strong growth, reflecting the increasing niche needs of businesses operating in a complex digital environment.

Use our Xing social network dataset, a career-oriented social networking site focused on the European Union. Identify and verify the best candidates for your company through strategic hiring and recruiting decisions. Depending on your needs, you can purchase the entire dataset or a customized subset. Popular use cases include: tracking talent movement, sourcing new talent, lead generation, and an alternative investment data source. The Xing social network dataset offers a complete overview of professionals with data points such as: name, company, experience, education, country, and more.

The global proxy network software market is projected to be worth XXX million by 2033, with a CAGR of XX% from 2025 to 2033. This growth is attributed to the increasing demand for data privacy and security, the growing adoption of cloud-based applications, and the rise of artificial intelligence (AI) and machine learning (ML). Key market drivers include the need for organizations to protect their sensitive data from cyberattacks, the growing use of cloud and SaaS applications, and the rise of AI and ML. Additionally, the increasing adoption of IoT devices and the growing demand for real-time data analytics are also contributing to the growth of the market. Major players in the market include Bright Data, Oxylabs, Zyte, Soax, NetNut, Smartproxy, Apify, PrivateProxy, Crawlbase (ProxyCrawl), LimeProxies, GeoSurf, Infatica, IPRoyal, FoxyProxy, Psiphon, and Artica Proxy.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Morphological images of cells contain extensive information, which help biologists to infer the type and state of cells to some degree based on their morphology. Convolutional Neural Network (CNN), a neural network architecture, is a powerful tool used for image recognition. However, whether it can be used to classify cells on the basis of their morphology remains unclear.We have obtained bright-field images of 10 human hematopoietic tumor-derived cell lines (including acute myeloid leukemia, chronic myeloid leukemia, B-cell acute lymphoblastic leukemia, and myeloma) by imaging flow cytometer (90,000 images per group). These data have been processed for use in Keras. Thus, we believe that these data could be useful for research in the field of cell biology using machine learning.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

SolarWinds (SWI) Poised for Growth: A Bright Future for the Network Management Leader

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This is replication data for the article 'Understanding news story chains using information retrieval and network clustering techniques', which will shortly appear in the journal Communication Methods and Measures.

This is the data repository for training and testing the Twin Network. The imaging data repositories are divided into several packages based on independent experiments. The data comprises bright-field time-lapse images of zebrafish embryos acquired in multiple batches within multi-well plates using an Acquifer Imaging Machine. Individual embryo segments were identified and extracted using a trained neural network for object detection. Within these experiment folders, data are organized by microscope position and embryo number.

Bright daylight has various positive influences, such as the long-term synchronization of circadian rhythms and an associated alertness that creates optimal conditions for attentional performance. However, the short-term effects of light on attention have not yet been sufficiently researched. Studies of these short-term effects on selective attention also showed partly contradictory effects. To investigate these short-term effects, 95 participants completed the Attention Network Test, under conditions of bright daylight or warm-white light. The focus of the present study was on executive attention, because this construct comes closest to the ANT short form of selective attention used. A significant enhancement of executive attention was observed under bright daylight conditions. This specifically means a short term effect of bright daylight on executive attention and thus selective attention in young adults.

The unprecedented impact of the pandemic on both activities and profit of actors draws out the various areas of the value chain that need to be strengthened to ensure resilience in the face of global shock. This study fills the gap by assessing the extent at which COVID-19 impacted the profit of mango value chain actors in southern Ghana. It also analyzed the governance structure and the existing linkages in the dissemination of market information in relation to the profit of the actors. A two-year panel survey on 240 respondents was conducted in 2020 through a multi-stage sampling technique in Greater Accra, Eastern and Volta regions of Ghana. Net Farm Income, Social Network Analysis and Difference-in-Difference models were used in analyzing the data. Findings revealed that mango processors have more bargaining power and make the most profit while producers receive more information than other actors. Farmer-based organizations were found to be the prominent node and influential in the dissemination of market information within the value chain. The outbreak of COVID-19 negatively impacted the profit of mango producers and distributors; however, processors had a positive impact on their profit. The study therefore demonstrated that producers and distributors were vulnerable to the effect of the COVID-19 shock, whilst processors were robust to the shocks. Thus, reformed policies by all stakeholders for emergency preparedness should be targeted especially at those vulnerable actors in the chain. Additionally, FBOs, retailers and other key stakeholders should be considered in policy development to enhance market information dissemination.