Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

• Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
• Global Reach: Access over 28 million verified company profiles across 195 countries.
• Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
• Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
• Real-Time Updates: Stay ahead with continuously updated company information.
• Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
• Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
• Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
• Market Research: Enrich your market intelligence initiatives by gain...

This Private Company Data dataset is a refined version of our company datasets, consisting of 35M+ data records.

It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B private company data. This data is also enriched by leveraging a carefully instructed large language model (LLM).

AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

Coresignal is a leading private company data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

As of 2023, most companies either agree or strongly agree to have a positive attitude towards data, analytics, and AI function. While most respondents claim to be able to attract the talent they need on a contract or project-specific basis, about ** percent of the respondents claim not to have adequate funding to build the data and analytics program their company needs.

Recent developments include: December 2023: TELUS International, a digital customer experience innovator in AI and content moderation, launched Experts Engine, a fully managed, technology-driven, on-demand expert acquisition solution for generative AI models. It programmatically brings together human expertise and Gen AI tasks, such as data collection, data generation, annotation, and validation, to build high-quality training sets for the most challenging master models, including the Large Language Model (LLM)., September 2023: Cogito Tech, a player in data labeling for AI development, launched an appeal to AI vendors globally by introducing a “Nutrition Facts” style model for an AI training dataset known as DataSum. The company has been actively encouraging a more Ethical approach to AI, ML, and employment practices., June 2023: Sama, a provider of data annotation solutions that power AI models, launched Platform 2.0, a new computer vision platform designed to reduce the risk of ML algorithm failure in AI training models., May 2023: Appen Limited, a player in AI lifecycle data, announced a partnership with Reka AI, an emerging AI company making its way from stealth. This partnership aims to combine Appen's data services with Reka's proprietary multimodal language models., March 2022: Appen Limited invested in Mindtech, a synthetic data company focusing on the development of training data for AI computer vision models. This investment is part of Appen's strategy to invest capital in product-led businesses generating new and emerging sources of training data for supporting the AI lifecycle.. Key drivers for this market are: Rapid Adoption of AI Technologies for Training Datasets to Aid Market Growth. Potential restraints include: Lack of Skilled AI Professionals and Data Privacy Concerns to Hinder Market Expansion. Notable trends are: Rising Usage of Synthetic Data for Enhancing Authentication to Propel Market Growth.

Top artificial intelligence firms are racing to build the biggest and most powerful Nvidia server chip clusters to win in AI. Below, we mapped the biggest completed and planned server clusters. Check back often, as we'll update the list when we confirm more data.

Success.ai’s LinkedIn Data Solutions offer unparalleled access to a vast dataset of 700 million public LinkedIn profiles and 70 million LinkedIn company records, making it one of the most comprehensive and reliable LinkedIn datasets available on the market today. Our employee data and LinkedIn data are ideal for businesses looking to streamline recruitment efforts, build highly targeted lead lists, or develop personalized B2B marketing campaigns.

Whether you’re looking for recruiting data, conducting investment research, or seeking to enrich your CRM systems with accurate and up-to-date LinkedIn profile data, Success.ai provides everything you need with pinpoint precision. By tapping into LinkedIn company data, you’ll have access to over 40 critical data points per profile, including education, professional history, and skills.

Key Benefits of Success.ai’s LinkedIn Data: Our LinkedIn data solution offers more than just a dataset. With GDPR-compliant data, AI-enhanced accuracy, and a price match guarantee, Success.ai ensures you receive the highest-quality data at the best price in the market. Our datasets are delivered in Parquet format for easy integration into your systems, and with millions of profiles updated daily, you can trust that you’re always working with fresh, relevant data.

Global Reach and Industry Coverage: Our LinkedIn data covers professionals across all industries and sectors, providing you with detailed insights into businesses around the world. Our geographic coverage spans 259M profiles in the United States, 22M in the United Kingdom, 27M in India, and thousands of profiles in regions such as Europe, Latin America, and Asia Pacific. With LinkedIn company data, you can access profiles of top companies from the United States (6M+), United Kingdom (2M+), and beyond, helping you scale your outreach globally.

Why Choose Success.ai’s LinkedIn Data: Success.ai stands out for its tailored approach and white-glove service, making it easy for businesses to receive exactly the data they need without managing complex data platforms. Our dedicated Success Managers will curate and deliver your dataset based on your specific requirements, so you can focus on what matters most—reaching the right audience. Whether you’re sourcing employee data, LinkedIn profile data, or recruiting data, our service ensures a seamless experience with 99% data accuracy.

• Best Price Guarantee: We offer unbeatable pricing on LinkedIn data, and we’ll match any competitor.
• Global Scale: Access 700 million LinkedIn profiles and 70 million company records globally.
• AI-Verified Accuracy: Enjoy 99% data accuracy through our advanced AI and manual validation processes.
• Real-Time Data: Profiles are updated daily, ensuring you always have the most relevant insights.
• Tailored Solutions: Get custom-curated LinkedIn data delivered directly, without managing platforms.
• Ethically Sourced Data: Compliant with global privacy laws, ensuring responsible data usage.
• Comprehensive Profiles: Over 40 data points per profile, including job titles, skills, and company details.
• Wide Industry Coverage: Covering sectors from tech to finance across regions like the US, UK, Europe, and Asia.

Key Use Cases:

• Sales Prospecting and Lead Generation: Build targeted lead lists using LinkedIn company data and professional profiles, helping sales teams engage decision-makers at high-value accounts.
• Recruitment and Talent Sourcing: Use LinkedIn profile data to identify and reach top candidates globally. Our employee data includes work history, skills, and education, providing all the details you need for successful recruitment.
• Account-Based Marketing (ABM): Use our LinkedIn company data to tailor marketing campaigns to key accounts, making your outreach efforts more personalized and effective.
• Investment Research & Due Diligence: Identify companies with strong growth potential using LinkedIn company data. Access key data points such as funding history, employee count, and company trends to fuel investment decisions.
• Competitor Analysis: Stay ahead of your competition by tracking hiring trends, employee movement, and company growth through LinkedIn data. Use these insights to adjust your market strategy and improve your competitive positioning.
• CRM Data Enrichment: Enhance your CRM systems with real-time updates from Success.ai’s LinkedIn data, ensuring that your sales and marketing teams are always working with accurate and up-to-date information.
• Comprehensive Data Points for LinkedIn Profiles: Our LinkedIn profile data includes over 40 key data points for every individual and company, ensuring a complete understanding of each contact:

LinkedIn URL: Access direct links to LinkedIn profiles for immediate insights. Full Name: Verified first and last names. Job Title: Current job titles, and prior experience. Company Information: Company name, LinkedIn URL, domain, and location. Work and Per...

This index compiles empirical data on AI and big data surveillance use for 179 countries around the world between 2012 and 2022— although the bulk of the sources stem from between 2017 and 2022. The index does not distinguish between legitimate and illegitimate uses of AI and big data surveillance. Rather, the purpose of the research is to show how new surveillance capabilities are transforming governments’ ability to monitor and track individuals or groups. Last updated February 2022.

This index addresses three primary questions: Which countries have documented AI and big data public surveillance capabilities? What types of AI and big data public surveillance technologies are governments deploying? And which companies are involved in supplying this technology?

The index measures AI and big data public surveillance systems deployed by state authorities, such as safe cities, social media monitoring, or facial recognition cameras. It does not assess the use of surveillance in private spaces (such as privately-owned businesses in malls or hospitals), nor does it evaluate private uses of this technology (e.g., facial recognition integrated in personal devices). It also does not include AI and big data surveillance used in Automated Border Control systems that are commonly found in airport entry/exit terminals. Finally, the index includes a list of frequently mentioned companies – by country – which source material indicates provide AI and big data surveillance tools and services.

All reference source material used to build the index has been compiled into an open Zotero library, available at https://www.zotero.org/groups/2347403/global_ai_surveillance/items. The index includes detailed information for seventy-seven countries where open source analysis indicates that governments have acquired AI and big data public surveillance capabilities. The index breaks down AI and big data public surveillance tools into the following categories: smart city/safe city, public facial recognition systems, smart policing, and social media surveillance.

The findings indicate that at least seventy-seven out of 179 countries are actively using AI and big data technology for public surveillance purposes:

• Smart city/safe city platforms: fifty-five countries • Public facial recognition systems: sixty-eight countries • Smart policing: sixty-one countries • Social media surveillance: thirty-six countries

The hyperscale data center industry is experiencing robust growth, projected to reach a market size of $101.23 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.29% from 2025 to 2033. This expansion is fueled by several key drivers. The exponential increase in data generated by cloud computing, the Internet of Things (IoT), and big data analytics necessitates massive data storage and processing capabilities, driving demand for hyperscale data centers. Furthermore, the increasing adoption of artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) applications further intensifies this demand. The shift towards digital transformation across various industries, coupled with the growing need for enhanced network connectivity and low latency, is also contributing significantly to market growth. Hyperscale colocation facilities are gaining traction, offering businesses a scalable and cost-effective alternative to self-build data centers. Competition among major players, including IBM, Hewlett Packard Enterprise, Alphabet, Cisco, Microsoft, Amazon Web Services, Huawei, Quanta Computer, Alibaba, Facebook, and Nvidia, is fierce, driving innovation and efficiency improvements within the sector. Geographical distribution reveals a strong presence in North America and Europe, driven by mature digital economies and robust IT infrastructure. However, the Asia-Pacific region is witnessing rapid growth, particularly in countries like India and China, fueled by increasing digitalization and government initiatives to support the development of digital infrastructure. Despite the positive growth trajectory, challenges remain. These include the high initial capital investment required for building and maintaining hyperscale data centers, the escalating energy consumption, and the growing concerns regarding data security and privacy. Addressing these challenges will be crucial for sustainable and responsible growth in the hyperscale data center market throughout the forecast period. The industry is likely to see further consolidation and strategic partnerships as companies seek to leverage economies of scale and expand their market reach. Recent developments include: November 2022 - Big Data Exchange (BDx), PT Indosat Tbk (Indosat Ooredoo Hutchison), and PT Aplikanusa Lintasarta announced their plan to build a 100MW data center complex on 12 acres of land. This new data center campus, CGK5, will be located in Karawang, West Java, east of Jakarta, and will be part of the company's third availability zone. The BDx Indonesia joint venture is a key component of the BDx platform, and the construction of CGK5 is BDx's 11th data center in the Asia-Pacific region. With more than USD 1 billion in committed investment funding, BDx's strong development trajectory across Asia allows scaled innovation in the most challenging markets., June 2022 - Equinix Inc., one of the leading global digital infrastructure companies, and PGIM Real Estate, the real estate investment and financing arm of PGIM, Prudential financial's global asset management business, announced the opening of the xScale data center in Sydney, named SY9x. This achievement followed the completion of the parties' USD 575 million joint venture., May 2022 - NTT Ltd in India announced the launch of its new hyperscale data center facility in Navi Mumbai, beginning with the NAV1A data center. This increases NTT's data center presence in the nation to 12 facilities, covering more than 2.5 million sq ft (232,258 m2) and 220 MW of facility power, solidifying its position as India's market leader in this segment., March 2022 - Yondr Group, one of the global leaders in developer, owner-operator, and service provider of data centers announced its expansion into the Malaysian market with a planned 200MW hyperscale campus to be developed on 72.8 acres of land acquired from TPM Technopark Sdn Bhd, a wholly owned subsidiary of Johor Corporation. Yondr's hyper-scale campus will be built in phases and have a total capacity of 200MW when completed, with the first phase anticipated to be completed in 2024. With at least 600MW of capacity, black fiber connectivity, and scalable utilities and infrastructure.. Key drivers for this market are: Growing Demand for Cloud Computing and Other High Performance Technologies. Potential restraints include: High Costs and Operational Concerns, Concerns related to Geoprivacy and Confidential Data. Notable trends are: Growing Demand for Cloud Computing and Other Hight Performance Technologies Driving the Market.

The Enterprise AI market is experiencing explosive growth, projected to reach a substantial size driven by the increasing adoption of AI across various industries. The 52.17% CAGR from 2019-2024 indicates a significant market expansion, fueled by several key factors. Businesses are increasingly leveraging AI-powered solutions for automation, predictive analytics, and improved decision-making. The cloud-based deployment model is gaining traction due to its scalability, cost-effectiveness, and accessibility, contributing to the market's rapid expansion. Major industries like manufacturing, automotive, BFSI, and IT & Telecommunications are early adopters, utilizing AI for process optimization, risk management, and customer experience enhancement. The competitive landscape is characterized by a mix of established tech giants (Amazon Web Services, IBM, Microsoft, Google) and specialized AI companies (AiCure, Sentient Technologies), fostering innovation and driving down costs. Despite the strong growth trajectory, certain challenges exist. Data security and privacy concerns, the need for skilled AI professionals, and the high initial investment costs can act as restraints. However, ongoing technological advancements, decreasing hardware costs, and growing awareness of AI's benefits are likely to mitigate these challenges. The market segmentation reveals a strong preference for cloud-based solutions, with the North American market currently holding a significant share due to early adoption and technological maturity. However, Asia and Europe are projected to witness substantial growth in the coming years driven by increasing digitalization initiatives and government support for AI development. The forecast period of 2025-2033 promises continued expansion, with specific segments like AI-powered customer service and predictive maintenance expected to demonstrate particularly high growth rates. This comprehensive report offers a detailed analysis of the Enterprise AI market, providing invaluable insights into its growth trajectory, key players, and future prospects. Covering the period from 2019 to 2033, with a base year of 2025, this study uses rigorous research methodologies to forecast market value in millions and provide actionable intelligence for businesses operating in this dynamic sector. The report segments the market by type (solution, service), deployment (on-premise, cloud), and end-user industry (manufacturing, automotive, BFSI, IT & telecommunication, media & advertising, others), offering a granular view of the competitive landscape. Recent developments include: September 2022: SAP updated the core of its SAP SuccessFactors Human Experience Management (HMX) Suite to give businesses a more effective means of implementing an integrated talent development strategy and building a workforce prepared for the future. To give companies a better understanding of the capabilities within their workforce and actionable talent intelligence to align their people with the organization's needs, the most recent developments to the SAP SuccessFactors HMX Suite combine data, machine learning, and artificial intelligence (AI)., February 2022: Enterprise artificial intelligence (AI) solutions startup, Mozn raised USD 10 million in a Series A funding round. Mozn provides enterprises make better mission-critical decisions through AI products and resolutions that leverage its proprietary state-of-the-art Arabic natural language understanding (NLU) platform and its cutting-edge risk and fraud engine.. Key drivers for this market are: Increasing Demand for Automation and AI-based Solutions, Increasing Need to Analyze Exponentially Growing Data Sets. Potential restraints include: Sluggish Adoption Rates. Notable trends are: Cloud Deployment is Expected to Experience a Significant Market Growth.

Artificial Intelligence in Logistics Market Outlook

The global artificial intelligence in logistics market size was valued at USD 5.8 billion in 2023 and is projected to reach USD 29.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 19.5% from 2024 to 2032. This explosive growth is driven by the increasing adoption of AI for enhancing operational efficiency, reducing costs, and providing superior customer service in the logistics industry.

One of the primary growth factors for AI in logistics is the increasing complexity of supply chains. As global trade continues to expand, supply chains have become more intricate and difficult to manage. AI offers solutions such as predictive analytics, real-time monitoring, and automated decision-making, which help logistics companies to anticipate issues, streamline operations, and enhance decision-making processes. Consequently, companies are investing heavily in AI technologies to stay competitive and meet the demands of modern supply chains.

Another significant driver is the rapid advancement in AI and machine learning technologies. Innovations in AI algorithms, increased computational power, and the availability of large volumes of data have made AI applications more effective and accessible. For instance, AI-powered robots and drones are increasingly being used for inventory management and delivery purposes, thereby reducing human errors and operational costs. Additionally, AI-based analytics tools enable logistics firms to gain insights into customer behaviors, optimize routes, and automate routine tasks, further boosting efficiency and profitability.

The rising demand for personalized customer experiences is also fueling the growth of AI in logistics. Consumers now expect faster deliveries, real-time tracking, and personalized services. AI enables logistics companies to meet these expectations by optimizing delivery routes, predicting shipment delays, and automating customer service tasks such as chatbots and virtual assistants. This not only improves customer satisfaction but also helps companies to build stronger customer relationships and loyalty.

Geographically, North America holds a significant share of the AI in logistics market, primarily due to the early adoption of advanced technologies and the presence of major logistics companies. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by rapid industrialization, increasing e-commerce activities, and substantial investments in AI research and development. Countries like China, India, and Japan are at the forefront of this growth, thanks to their expanding logistics networks and favorable government policies supporting AI adoption.

Component Analysis

The component segment of the AI in logistics market is divided into software, hardware, and services. Each component plays a crucial role in the implementation and success of AI technologies in the logistics industry. The software segment includes AI platforms, analytics tools, and machine learning algorithms that facilitate various logistics operations. As the backbone of AI applications, software solutions are essential for data processing, predictive analytics, and automation, making this segment the largest contributor to the market. Continuous advancements in software capabilities and the emergence of new AI applications are expected to drive significant growth in this segment.

The hardware segment encompasses various physical devices such as sensors, drones, robots, and IoT devices that enable AI functionalities in logistics. These devices collect data, perform tasks, and interact with the physical environment, making them integral to AI applications like inventory management, automated warehousing, and last-mile delivery. With the increasing adoption of robotics and IoT in logistics, the demand for advanced hardware solutions is on the rise. Innovations in sensor technology, robotics, and IoT are expected to further enhance the capabilities and efficiency of AI-driven logistics operations.

The services segment includes consulting, integration, and maintenance services that support the deployment and ongoing management of AI technologies in logistics. As companies embrace AI, they require expert guidance and support to implement these technologies effectively. Consulting services help organizations identify suitable AI solutions, develop strategies, and ensure seamless integration with existing systems. Additionally, maintenance services are crucial for the continuous functioning and optim

Dimensions is the largest database of research insight in the world. It represents the most comprehensive collection of linked data related to the global research and innovation ecosystem available in a single platform. Because Dimensions maps the entire research lifecycle, you can follow academic and industry research from early stage funding, through to output and on to social and economic impact. Businesses, governments, universities, investors, funders and researchers around the world use Dimensions to inform their research strategy and make evidence-based decisions on the R&D and innovation landscape. With Dimensions on Google BigQuery, you can seamlessly combine Dimensions data with your own private and external datasets; integrate with Business Intelligence and data visualization tools; and analyze billions of data points in seconds to create the actionable insights your organization needs. Examples of usage: Competitive intelligence Horizon-scanning & emerging trends Innovation landscape mapping Academic & industry partnerships and collaboration networks Key Opinion Leader (KOL) identification Recruitment & talent Performance & benchmarking Tracking funding dollar flows and citation patterns Literature gap analysis Marketing and communication strategy Social and economic impact of research About the data: Dimensions is updated daily and constantly growing. It contains over 112m linked research publications, 1.3bn+ citations, 5.6m+ grants worth $1.7trillion+ in funding, 41m+ patents, 600k+ clinical trials, 100k+ organizations, 65m+ disambiguated researchers and more. The data is normalized, linked, and ready for analysis. Dimensions is available as a subscription offering. For more information, please visit www.dimensions.ai/bigquery and a member of our team will be in touch shortly. If you would like to try our data for free, please select "try sample" to see our openly available Covid-19 data.Learn more

In 2023, close to *** out of ten global industry decision-makers had already integrated generative artificial intelligence to generate product recommendations utilized by associates in physical stores. Meanwhile, ** percent were in the process of evaluating its adoption. Moreover, ** percent employed generative Artificial Intelligence (AI) to develop conversational digital shopping assistants, ** percent utilized it for constructing virtual models for product pages, and ** percent applied it to curate personalized product bundles. AI-driven personalization Utilizing artificial intelligence to craft personalized shopping experiences has become a cornerstone strategy for e-commerce retailers. In 2023, **** of ten businesses surveyed worldwide employed AI-driven personalization to fuel growth. To measure the success of AI in personalization, companies primarily look at the accuracy and speed of real-time data alongside metrics like customer retention and repeat purchases. As AI technologies advance, the potential for increasingly refined and impactful personalization within e-commerce will expand even further. The consumer experience AI helps e-commerce businesses understand and respond to consumers' preferences, needs, and behaviors. One crucial area of online shopping where people anticipate AI improvements is price comparison, as indicated by **** of the participants in a 2023 survey. Consequently, consumers are eager to uncover relevant promotions, offers, and products. However, the swift pace of these advancements also breeds skepticism among online shoppers, especially among older demographics, many of whom express discomfort with this technology's use for personalization.

Canadian data processing and hosting services are in a phase of rapid transformation driven by increasing reliance on cloud computing, accelerated digital demand, combined with a pressing need for robust cybersecurity measures. Datacenter owners have benefited from substantial public sector support, particularly tax breaks and subsidies, aligning the sector's growth trajectory with national economic priorities. These support mechanisms have allowed datacenter companies to build large data complexes, critical for sustaining the new digital economy's infrastructure, and helping the industry to grow at a dramatic CAGR of 8.8% to $16.1 billion in 2024, when revenue will expand 1.4% and profit will center at 7.6%. The rise in cloud computing has been a watershed moment, redefining how businesses manage and access their data. Data processors benefit as companies continue to outsource IT needs to streamline operations and cut costs. The market's crowded nature and high barriers to entry, such as legal compliance and startup costs, make differentiation necessary. Leading companies are navigating these challenges by pivoting to niche markets like healthcare and defense that require specialized compliance and security features. Competition dynamics also hinge on the power balance between buyers and suppliers. High buyer power is evident, particularly from sectors like IT consulting and software publishing, driving data providers to secure long-term contracts and customizable solutions to reduce churn. Meanwhile, hardware suppliers exert significant influence, particularly in segments requiring advanced technologies like AI. Some industry leaders are advancing toward vertical integration by developing proprietary hardware to mitigate this. The Canadian data processing landscape anticipates moderate but steady growth at a CAGR of 1.5% and will attempt to reach $17.4 billion. Embracing emerging technologies such as AI and machine learning will be crucial for success. Moreover, focusing on sustainability through renewable energy sources can help manage operational costs while enhancing corporate reputation. Providing scalable, secure, and innovative data solutions will empower operators to meet domestic and international client demands, ensuring competitiveness and resilience in an increasingly digital world.

Data Integration Market Outlook 2032

The global data integration market size was USD 13.33 Billion in 2023 and is likely to reach USD 36.76 Billion by 2032, expanding at a CAGR of 11.93 % during 2024–2032. The market growth is attributed to the growing need for businesses to comply with various regulatory requirements and the increasing demand for real-time data.



Increasing demand for real-time data is expected to boost the global data integration market. Real-time data allows businesses to make decisions quickly and accurately. However, to make the most of this data, it needs to be integrated with other data sources to provide a complete picture. This is where data integration comes in, enabling businesses to combine data from different sources and make informed decisions. Therefore, the rising demand for real-time data is propelling the market.



Data integration solutions are widely used in several industries including BFSI, healthcare, IT & telecom, retail, manufacturing, and others as these solutions allow businesses for better analysis and insights, leading to effective strategies and actions. Additionally, data integration automates the process of gathering, combining, and processing data. This saves time and reduces the risk of errors compared to manual data handling. These benefits offered by data integration solutions encourage industries to deploy these solutions into their operation for better decision-making.

Impact of Artificial Intelligence (AI) in Data Integration Market

Artificial Intelligence (AI) is revolutionizing the data integration market by automating and optimizing the process of combining data from different sources. AI algorithms identify patterns and relationships in data, enabling them to accurately map and integrate data from various sources. This not only reduces

The size of the Global Artificial Intelligence in Diagnostics Market was valued at USD 1.33 Million in 2023 and is projected to reach USD 9.86 Million by 2032, with an expected CAGR of 33.14% during the forecast period. The growth of the artificial intelligence (AI) in diagnostics market is highly felt globally as AI technologies continue to revolutionize healthcare sectors. In the diagnostics sector, AI plays more significant roles, and healthcare research companies combine it with diagnostic tools to make disease detection highly accurate, efficient, and faster. With powerful machine learning algorithms and sophisticated data analytics, AI can scan masses of medical data-anything from medical images to patient histories and genetic information-much better and often more accurately than could be done traditionally. This is particularly important in fields like radiology, pathology, and ophthalmology, where early detection of such conditions as cancer, heart disease, and neurological disorders can easily lead to much better patient outcomes. The significant drivers for this market comprise the growing adoption of AI-powered diagnostic tools in hospitals and healthcare facilities worldwide, and the steadily increasing demand for personalized medicine. In fact, AI technologies can actually identify patterns that human doctors miss, which would make it a great asset for improving diagnostic precision and reducing human error. Moreover, as healthcare systems are getting squeezed to produce cheaper care, AI solutions are being hailed as an answer to workflow optimization and reduced operational costs. Recent developments include: In June 2022, Bayer launched Calantic digital solutions to help address radiology industry challenges. The new platform includes apps to assist radiologists with workload management, lesion detection, and patient management. Bayer expanded the digital capabilities of its radiology business with the launch of artificial intelligence-based apps for X-ray, MRI, and CT imaging., In October 2021, Roche entered into an agreement with PathAI for pathology. Under the development and distribution agreement, the companies will jointly develop pathologists' embedded image analysis workflow.. Key drivers for this market are: Increasing Demand For AI Tools in the Medical Imaging Field and Rising Focus On Reducing the Workload of Radiologists, Government Initiative to Increase the Adoption Of AI-Based Technologies; Growth in Funding for AI-Based Start-Ups. Potential restraints include: Reluctance Among Medical Practitioners to Adopt AI-Based Technologies, High Procurement Costs and Maintenance. Notable trends are: X-rays Segment is Expected to Dominate the Market.

According to Cognitive Market Research, the global Ai Platform market size will be USD 8512.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 30.50% from 2023 to 2030.

The demand for AI platforms is rising due toincreased adoption of enterprise AI solutions and advancements in AI technologies and algorithms.
Demand for Services remains higher in the AI platform market.
The cloud category held the highest AI platform market revenue share in 2023.
North American AI platformwill continue to lead, whereas the Asia-PacificAI platform market will experience the most substantial growth until 2030.

Market Dynamics of AI Platform Market

Key Drivers of AI Platform Market

Accelerated Digital Transformation Initiatives to Provide Viable Market Output

One key driver in the AI Platform market is the accelerated pace of digital transformation initiatives across industries. As organizations strive to remain competitive in a rapidly evolving digital landscape, the demand for AI platforms has surged. These platforms offer a comprehensive suite of tools and services to facilitate the development and deployment of AI applications, enabling businesses to harness the power of artificial intelligence for improved decision-making, operational efficiency, and enhanced customer experiences. The imperative to digitize processes and leverage AI capabilities to gain a competitive edge has become a primary driver propelling the growth of the AI Platform market.

In May 2023, An improvement to the HPE Ezmeral Software platform was announced by HPE. From the edge to the cloud, HPE Ezmeral Software extends HPE GreenLake's data and analytics capabilities.

(Source: www.hpe.com/us/en/newsroom/press-release/2023/05/hpe-ezmeral-software-accelerates-and-simplifies-analytics-and-aiml-initiatives-with-significant-advances-to-the-hybrid-multi-cloud-data-and-analytics-platform.html)

Increasing Focus on AI-Driven Innovation to Propel Market Growth

The increasing emphasis on AI-driven innovation serves as another key driver for the AI Platform market. Organizations are recognizing the transformative potential of AI in unlocking new business opportunities, driving efficiency, and fostering innovation. AI platforms play a pivotal role by providing the necessary infrastructure and tools for developers and data scientists to experiment, build, and deploy advanced AI models. As businesses seek to harness the full spectrum of AI capabilities, from machine learning to natural language processing, the demand for versatile and scalable AI platforms continues to grow. The focus on AI-driven innovation as a strategic imperative acts as a significant driver shaping the dynamics of the AI Platform market.

In April 2023, IBM Security QRadar Suite, which was just released, aims to enhance and expedite the security analyst experience during an incident.

(Source: newsroom.ibm.com/2023-04-24-IBM-Launches-New-QRadar-Security-Suite-to-Speed-Threat-Detection-and-Response)

Restraint Factors Of xyz Market AI Platform Market

Data Privacy and Security Concerns to Restrict Market Growth

A primary restraint in the AI Platform market is the heightened awareness and concern regarding data privacy and security. As AI platforms heavily rely on vast datasets for training and optimization, the collection and handling of sensitive information pose significant challenges. Organizations and users alike are increasingly wary of potential data breaches, unauthorized access, and ethical implications associated with AI-driven applications. The need for robust privacy measures, transparent data governance, and stringent security protocols becomes crucial in mitigating these concerns and fostering trust in AI platforms, impacting the market dynamics by necessitating a delicate balance between innovations and safeguarding user data.

Impact of COVID–19 on The AI Platform Market

The COVID-19 pandemic has had a mixed impact on the AI Platform market. While the initial phases of the pandemic led to disruptions in some industries, the overall effect on the AI Platform market has been positive. The crisis accelerated digital transformation efforts across various sectors, prompting businesses to prioritize automation, data analytics, and AI technologies to adapt to remote work environments and enhance operational efficiency. The increased focus on AI-driven solutio...

The North America data center construction market, valued at $22.40 billion in 2025, is projected to experience robust growth, driven by a Compound Annual Growth Rate (CAGR) of 6.20% from 2025 to 2033. This expansion is fueled by several key factors. The increasing demand for cloud computing and digital services necessitates substantial investment in data center infrastructure. Organizations across various sectors, including banking, financial services, insurance (BFSI), IT and telecommunications, and government, are aggressively expanding their data center footprints to support growing data volumes and enhance operational efficiency. Furthermore, the adoption of advanced technologies like artificial intelligence (AI) and machine learning (ML) further accelerates this demand. The market is segmented by infrastructure type (electrical and mechanical), tier type (Tier I-IV), and end-user industry. Electrical infrastructure, encompassing power distribution solutions (PDUs, transfer switches, switchgear), power backup solutions (UPS, generators), and related services, constitutes a significant portion of the market. Mechanical infrastructure, including cooling systems (immersion, direct-to-chip, rear door heat exchangers, in-row/in-rack), racks, and other components, is equally crucial for maintaining optimal data center operations. The significant players in this market include AECOM, Whiting-Turner Contracting Company, Turner Construction Co, Jacobs Solutions Inc, and others, competing intensely based on their expertise, project delivery capabilities, and technological innovations. Growth is expected to be particularly strong in the Tier III and Tier IV data center segments, reflecting the increasing focus on high-availability and resilience. While the United States dominates the North American market, Canada and Mexico are also experiencing growth, driven by increasing digitalization and foreign investment. However, the market faces certain challenges, including rising construction costs, supply chain disruptions, and the need for skilled labor. Despite these restraints, the long-term outlook remains positive, with continued growth anticipated throughout the forecast period driven by sustained demand for advanced data center facilities across all major sectors. The market's success is intertwined with the continued advancement of digital technologies and the unwavering need for robust and reliable data storage and processing capabilities. Recent developments include: January 2024: The ACS group was selected to build a hyperscale data center campus for meta in Jeffersonville, Indiana, through Turner Construction Company. The nearly 700,000-square-foot campus is expected to feature several data center buildings. Once completed, the Jeffersonville data center is anticipated to cost over USD 800 million to build., October 2023: JLL, Lumen Technologies, and Schneider Electric are expected to offer customers around the United States modular data centers. JLL is anticipated to identify and select locations for the initiative, including approximately 5,000 sites across Lumen's fiber network. Schneider Electric brings its expertise in design and construction, with the agreement aiming to have ready-to-use modular data centers available in six to nine months.. Key drivers for this market are: 4., Growing Cloud Applications, AI, and Big Data4.; Rising Adoption of Hyperscale Data Centers. Potential restraints include: 4., Growing Cloud Applications, AI, and Big Data4.; Rising Adoption of Hyperscale Data Centers. Notable trends are: United States to hold the Major Market Share.

Analysis of ‘🍕 Pizza restaurants and Pizzas on their Menus’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/pizza-restaurants-and-pizzas-on-their-menuse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

About this Data

This is a list of over 3,500 pizzas from multiple restaurants provided by Datafiniti's Business Database. The dataset includes the category, name, address, city, state, menu information, price range, and more for each pizza restaurant.

Note that this is a sample of a large dataset. The full dataset is available through Datafiniti.

What You Can Do with this Data

You can use this data to discover how much you can expect to pay for pizza across the country. E.g.:

• What are the least and most expensive cities for pizza?
• What is the number of restaurants serving pizza per capita (100,000 residents) across the U.S.?
• What is the median price of a large plain pizza across the U.S.?
• Which cities have the most restaurants serving pizza per capita (100,000 residents)?

Data Schema

A full schema for the data is available in our support documentation.

About Datafiniti

Datafiniti provides instant access to web data. We compile data from thousands of websites to create standardized databases of business, product, and property information. Learn more.

Interested in the Full Dataset?

Get this data and more by creating a free Datafiniti account or requesting a demo.

This dataset was created by Datafiniti and contains around 10000 samples along with Longitude, Price Range Max, technical information and other features such as: - Date Updated - Categories - and more.

How to use this dataset

• Analyze Date Added in relation to Province
• Study the influence of Price Range Min on Address
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Datafiniti

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Build Design Data Center Market Outlook

The global market size for Build Design Data Centers was valued at USD 40 billion in 2023 and is projected to reach USD 85 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 8.5%. The market's robust growth is primarily driven by the escalating demand for cloud-based services, the proliferation of Internet of Things (IoT) devices, and the increasing necessity for data storage solutions across various industries.

One of the primary growth factors for the Build Design Data Center market is the exponential increase in data generation. With the advent of big data analytics, artificial intelligence, and machine learning, organizations are generating massive amounts of data that require efficient and scalable storage solutions. This surge in data generation is compelling companies to invest heavily in data center infrastructure, thereby driving the market's growth. Additionally, the rapid digital transformation across industries is augmenting the need for robust and scalable data centers to manage and process data efficiently.

Another significant growth factor is the rising adoption of cloud computing services. Businesses are increasingly transitioning from on-premises data centers to cloud-based solutions due to the latter's scalability, cost-efficiency, and flexibility. This shift is leading to an increased demand for data centers that can support cloud infrastructures. Furthermore, the increasing popularity of hybrid cloud solutions, which combine private and public cloud environments, is also contributing to the market's expansion.

The proliferation of IoT devices is also playing a crucial role in driving the Build Design Data Center market. IoT devices generate vast amounts of data that need to be stored, analyzed, and processed in real-time. Data centers with advanced infrastructure and capabilities are essential to handle the data influx from IoT devices. The growing reliance on IoT across various sectors such as healthcare, manufacturing, and retail is thereby fueling the demand for state-of-the-art data centers.

In the context of evolving data center needs, the concept of a Multi-tenant Wholesale Data Center is gaining traction. These facilities offer shared infrastructure that can be utilized by multiple organizations, providing a cost-effective solution for businesses looking to expand their data storage capabilities without the burden of constructing their own data centers. Multi-tenant data centers are particularly appealing to companies that require scalable solutions to accommodate fluctuating data demands. By sharing resources such as power, cooling, and security, businesses can achieve significant cost savings while maintaining high levels of reliability and performance. This model also allows for greater flexibility in terms of space and capacity, enabling organizations to scale their operations seamlessly as their data needs grow.

Regionally, North America holds a significant share of the Build Design Data Center market, attributed to the presence of major technology companies and the rapid adoption of advanced technologies. The Asia Pacific region, however, is expected to witness the highest growth rate over the forecast period. Factors such as increasing internet penetration, the rise of digital economies, and substantial investments in IT infrastructure are driving the market in this region. Additionally, government initiatives to promote digitalization and smart city projects are further propelling the demand for data centers in the Asia Pacific.

Component Analysis

The Build Design Data Center market is segmented by components into Hardware, Software, and Services. Hardware components include servers, storage devices, networking equipment, and cooling systems, which form the backbone of data center infrastructure. The demand for advanced hardware components is driven by the need to handle increasing data volumes, enhance processing speeds, and improve overall efficiency. Innovations in hardware technology, such as the development of energy-efficient servers and high-capacity storage devices, are further boosting the market's growth.

Software components in data centers are crucial for managing and optimizing the infrastructure. This includes data center infrastructure management (DCIM) software, virtualization software, and security software. The growing emphasis on automation and the need for e

Investor Relations Tools Market Outlook

The global investor relations tools market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach around USD 5.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.5% during the forecast period. The market's growth is primarily driven by increasing demand for efficient communication and transparency between investors and companies. This growth is fueled by the rising complexity of financial markets, stricter regulatory requirements, and the need for companies to build and maintain strong relationships with their investors. Additionally, technological advancements and the proliferation of digital communication channels have further accelerated the adoption of investor relations tools.

One of the significant growth factors for the investor relations tools market is the increasing emphasis on corporate governance and compliance. Companies are under immense pressure to adhere to regulatory standards and provide timely, accurate information to their stakeholders. This has led to a surge in demand for tools that streamline and automate investor relations processes, ensuring compliance with various regulations such as the Sarbanes-Oxley Act and GDPR. These tools help organizations manage investor communications, track regulatory changes, and generate comprehensive reports, thus enhancing transparency and trust among investors.

Another driving force behind the market's expansion is the growing importance of investor engagement and relationship management. In today's competitive business environment, companies must foster strong relationships with their investors to secure funding and maintain a positive market image. Investor relations tools enable companies to efficiently manage communications, conduct virtual meetings, and provide real-time updates on financial performance, strategic initiatives, and market developments. This enhanced engagement helps companies build credibility and trust, ultimately leading to increased investor confidence and loyalty.

Technological advancements have also played a crucial role in the growth of the investor relations tools market. The adoption of artificial intelligence (AI), machine learning, and big data analytics has revolutionized the way companies manage their investor relations. These technologies enable organizations to analyze vast amounts of data, identify trends, and gain valuable insights into investor behavior and sentiment. By leveraging advanced analytics, companies can make informed decisions, personalize investor communications, and proactively address potential issues, thereby improving overall investor relations.

From a regional perspective, North America holds the largest share of the investor relations tools market, driven by the presence of numerous large enterprises, advanced technological infrastructure, and stringent regulatory requirements. The Asia Pacific region is expected to witness significant growth during the forecast period, owing to the rapid economic development, increasing number of publicly listed companies, and growing awareness about the importance of investor relations. Europe and Latin America are also projected to experience steady growth, supported by favorable regulatory environments and the adoption of digital technologies in investor relations.

Component Analysis

The investor relations tools market can be segmented by component into software and services. The software segment includes various applications designed to streamline and automate investor relations processes, such as investor relationship management (IRM) software, reporting tools, and communication platforms. These software solutions offer features like real-time data analytics, customizable dashboards, and automated reporting, which help companies enhance transparency, improve efficiency, and maintain compliance with regulatory requirements. The growing demand for these advanced software solutions is a key driver for the market's expansion.

Investor relations services encompass a wide range of offerings, including consulting, training, and support services provided by third-party vendors or specialized agencies. These services play a crucial role in helping companies develop and implement effective investor relations strategies, manage regulatory compliance, and optimize their communication efforts. The increasing complexity of financial markets and the need for expert g