five

Canaria | Startup Data | USA | +300000 Unique Companies & 2 Years Historical Startup Data | Industry classification with NAICS - SOC - SIC|初创公司数据数据集|市场分析数据集

收藏
Datarade2024-06-22 收录
初创公司数据
市场分析
下载链接:
https://datarade.ai/data-products/canaria-startup-data-usa-300000-unique-companies-2-y-canaria-inc
下载链接
链接失效反馈
资源简介:
Advanced Processing, Superior Insights Utilizing state-of-the-art AI and large language models (LLMs) validated by human experts, we are dedicated to delivering high-quality, actionable data through innovative technology. Apart from the models included in our standard data offerings, we have developed additional models to provide tailored results to your needs, such as a sentiment analysis model that analyzes text data to gauge sentiment, helping businesses understand public perception and employee feedback, anomaly detection models, and LLM-based summarization models that condense large chunks of text for you. Our Models: • Deduplication Model: Our model first removes exact duplicate records, then uses advanced AI to identify and eliminate near-duplicate job postings across different URLs, achieving approximately a 60% deduplication rate. • Title Taxonomy Model: With over 20 million unique job titles in our 500M+ job postings database, analysis can be challenging. Our AI models categorize each job posting into one of 50,000 standardized job titles from our internal normalized title taxonomy, simplifying data analysis. • Skill Taxonomy Model: Our in-house AI model identifies key entities in job postings, including hard skills, soft skills, certifications, and qualifications. Unlike keyword-based approaches, our model not only finds relevant keywords but also excludes irrelevant ones, ensuring precise data (e.g., "Hepatitis B" is skill for nursing jobs but not for accounting jobs). • Job Category Model: Our AI models analyze job descriptions, entities, predicted salary, location, industry, and job title to determine the seniority level of a job, standardizing levels across different companies. Another model identifies if a job is remote, onsite, or hybrid, accounting for discrepancies between job classifications and descriptions (e.g., a job classified as onsite but open to remote). • Salary Estimation Model: Using company salary history, industry ranges, location, seniority, and public government data, our models predict the salary range for job postings. • Government Classification Models: We developed models to classify job postings into Standard Occupation Codes (SOC) by the BLS and to categorize companies into industries based on their job posting information. Canaria's Startup Data is unparalleled in its depth, accuracy, and comprehensiveness. Our startup data product offers detailed information on startups, including names, URLs, addresses, industries, revenues, employee counts, and more. We pride ourselves on the precision of our geographical startup data, including latitude, longitude, city, state, and zip code information, enabling accurate location-based analysis. Our startup data is updated regularly, ensuring users always have access to the most current and reliable information. This commitment to accuracy and relevance sets Canaria's Startup Data apart from other products on the market. Furthermore, our extensive coverage spans a wide range of industries and countries, providing users with a global perspective essential for thorough market analysis and strategic decision-making. Canaria's Startup Data is sourced from a combination of public records, proprietary databases, industry reports, and direct submissions from startups. This multi-source approach ensures a high level of accuracy and completeness. We employ rigorous validation processes, including automated checks and manual reviews, to further enhance the quality of our startup data. Our sourcing strategy not only ensures comprehensive coverage but also maintains the integrity and reliability of the startup data. Market Analysis: • Identify Emerging Trends: Use our startup data to uncover trends within specific industries and geographical regions. • Assess Market Dynamics: Gain a deep understanding of market conditions and competitive landscapes using our startup data. Competitive Benchmarking: • Compare Against Industry Peers: Benchmark your company's performance metrics against those of industry leaders using our detailed startup data. • Gain Competitive Insights: Identify strengths and weaknesses relative to competitors with our startup data. Targeted Marketing: • Segment and Target Clients: Utilize our startup data to create precise segments and target potential clients effectively. • Personalize Marketing Campaigns: Tailor your marketing strategies based on detailed startup profiles. Geographical Analysis: • Develop Location-Based Strategies: Leverage geographical startup data to identify optimal regions for business expansion and strategy development. • Analyze Regional Industry Distribution: Understand the distribution of industries across different regions with our startup data. Academic Research: • Support Comprehensive Studies: Provide researchers with high-quality startup data to support in-depth academic research. • Generate Insights: Facilitate the generation of insights through detailed and accurate startup data. Business Reporting: • Generate Insightful Reports: Use our startup data to produce detailed reports on market conditions and competitive landscapes for stakeholders. • Inform Strategic Decisions: Support strategic business decisions with reliable and comprehensive startup data. Canaria's Startup Data product is a cornerstone of our broader data ecosystem, which includes various specialized datasets tailored for specific business needs. By integrating our startup data with other offerings, such as industry-specific insights, economic indicators, and consumer behavior data, we provide a holistic view that empowers businesses to make well-rounded, strategic decisions. Our commitment to data quality and comprehensiveness ensures that all our products meet the highest standards, offering unparalleled value to our customers. Our broader data offering includes tools and services that complement the startup data, such as advanced analytics, data visualization, and custom reporting solutions. These additional resources enable our clients to maximize the value of the startup data and apply it effectively across various business functions. Whether you are conducting market research, developing marketing strategies, or making investment decisions, Canaria's comprehensive data solutions are designed to support your objectives and drive success. Canaria's commitment to data privacy and security is demonstrated through our extensive certifications: • ePrivacyseal • Future of Privacy Forum (FPF) • International Association of Privacy Professionals (IAPP) • IAB Europe GDPR Transparency & Consent Framework • IAPP Certified Information Privacy Technologist (CIPT) • Privacy Shield Framework These certifications underscore our dedication to maintaining the highest standards of data privacy and security. Experience the power of Canaria's Startup Data by exploring our platform, requesting a personalized demo, or starting a free trial today. Discover how our high-quality, comprehensive startup data can elevate your business intelligence and drive your strategic initiatives. Visit our website to learn more about our startup data solutions and how they can benefit your business. Join the ranks of businesses that trust Canaria for their startup data needs and take your business intelligence to the next level.
提供机构:
Canaria Inc.
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

CMAB

CMAB数据集由清华大学创建,是中国首个全国范围的多属性建筑数据集,涵盖了3667个自然城市,总面积达213亿平方米。该数据集通过集成多源数据,如高分辨率Google Earth影像和街景图像,生成了建筑的屋顶、高度、功能、年龄和质量等属性。数据集的创建过程结合了地理人工智能框架和机器学习模型,确保了数据的高准确性。CMAB数据集主要应用于城市规划和可持续发展研究,旨在提供详细的城市3D物理和社会结构信息,支持城市化进程和政府决策。

arXiv 收录

UniMed

UniMed是一个大规模、开源的多模态医学数据集,包含超过530万张图像-文本对,涵盖六种不同的医学成像模态:X射线、CT、MRI、超声、病理学和眼底。该数据集通过利用大型语言模型(LLMs)将特定模态的分类数据集转换为图像-文本格式,并结合现有的医学领域的图像-文本数据,以促进可扩展的视觉语言模型(VLM)预训练。

github 收录

CatMeows

该数据集包含440个声音样本,由21只属于两个品种(缅因州库恩猫和欧洲短毛猫)的猫在三种不同情境下发出的喵声组成。这些情境包括刷毛、在陌生环境中隔离和等待食物。每个声音文件都遵循特定的命名约定,包含猫的唯一ID、品种、性别、猫主人的唯一ID、录音场次和发声计数。此外,还有一个额外的zip文件,包含被排除的录音(非喵声)和未剪辑的连续发声序列。

huggingface 收录

TCIA

TCIA(The Cancer Imaging Archive)是一个公开的癌症影像数据集,包含多种癌症类型的医学影像数据,如CT、MRI、PET等。这些数据通常与临床和病理信息相结合,用于癌症研究和临床试验。

www.cancerimagingarchive.net 收录

CE-CSL

CE-CSL数据集是由哈尔滨工程大学智能科学与工程学院创建的中文连续手语数据集,旨在解决现有数据集在复杂环境下的局限性。该数据集包含5,988个从日常生活场景中收集的连续手语视频片段,涵盖超过70种不同的复杂背景,确保了数据集的代表性和泛化能力。数据集的创建过程严格遵循实际应用导向,通过收集大量真实场景下的手语视频材料,覆盖了广泛的情境变化和环境复杂性。CE-CSL数据集主要应用于连续手语识别领域,旨在提高手语识别技术在复杂环境中的准确性和效率,促进聋人与听人社区之间的无障碍沟通。

arXiv 收录