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.

You can check the fields description in the documentation: current Keyword database: https://docs.dataforseo.com/v3/databases/google/keywords/?bash; Historical Keyword database: https://docs.dataforseo.com/v3/databases/google/history/keywords/?bash. You don’t have to download fresh data dumps in JSON or CSV – 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.

This dataset is about book subjects. It has 5 rows and is filtered where the books is Structured search for big data : from keywords to key-objects. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Abstract The era of big data is yet a reality for businesses and individuals. In recent year, the academic literature exploring this field has grown rapidly. This article aimed to identify the main fields and features of the published papers about big data analytics. The methodological approach considered was a bibliometric research at the ISI Web of Science platform, whose focus was given to the big data management issues. It was possible to identify five distinct groups within the published papers: evolution of big data; management, business and strategy; human behavior and the social and cultural aspects; data mining and knowledge generation; Internet of Things. It was possible to conclude that big data corresponds to an emerging theme, which is not yet consolidated. There is a wide variation in the terms used, which influences the bibliographic searches. Therefore, as a complimentary contribution of this research, the main keywords used in such articles were identified, which contributes for bibliometric research of future studies.

The Streaming Analytics Platform market is experiencing rapid growth, fueled by the increasing volume of real-time data generated across diverse industries. The market's Compound Annual Growth Rate (CAGR) of 32.67% from 2019 to 2024 indicates significant expansion, projected to continue in the forecast period (2025-2033). Key drivers include the need for businesses to gain actionable insights from streaming data to improve operational efficiency, enhance customer experiences, and drive better decision-making. The rise of cloud-based deployments simplifies implementation and reduces infrastructure costs, further accelerating market adoption. While the market is dominated by established players like IBM, Microsoft, and SAP, several smaller companies are innovating within specific niches, particularly in areas like specialized algorithms and industry-specific solutions. Growth is particularly strong in sectors such as media and entertainment, BFSI, and retail, which generate and rely heavily on real-time data analysis for personalization, fraud detection, and risk management. The on-premise segment, while still relevant, is witnessing a steady shift toward cloud-based solutions due to scalability and cost advantages. Geographic distribution shows a strong presence in North America and Europe, but the Asia-Pacific region is projected to exhibit high growth rates due to increased digitalization and technological advancements. The competitive landscape is characterized by a mix of established technology vendors and specialized startups. While large companies offer comprehensive platforms, smaller firms focus on specific functionalities or industry-verticals. This dynamic environment drives innovation and allows businesses to select solutions tailored to their specific needs. Future growth will likely be shaped by advancements in artificial intelligence (AI) and machine learning (ML) integration within streaming analytics platforms. This integration will enable more sophisticated data processing, predictive analytics, and automated insights generation. The increasing emphasis on data security and privacy regulations will also influence platform development and market adoption, driving demand for robust security features and compliance capabilities. Overall, the Streaming Analytics Platform market presents substantial opportunities for both established and emerging players, offering significant potential for investment and innovation. This in-depth report provides a comprehensive analysis of the global Streaming Analytics Platform market, projecting a robust growth trajectory from 2025 to 2033. The study covers the historical period (2019-2024), uses 2025 as the base year, and offers detailed estimations for the forecast period (2025-2033). The market is valued in millions of USD, offering crucial insights for businesses operating in or planning to enter this dynamic sector. Keywords: Streaming analytics, real-time analytics, big data analytics, cloud-based analytics, data streaming, real-time data processing, analytics platform, data processing platform. Key drivers for this market are: , Increasing Adoption of Advanced Analytic Tools by SMEs; Increasing Adoption of Cloud Services and IoT Applications; Growing Industrial Automation. Potential restraints include: , Stringent Government Regulations on Data Security. Notable trends are: Retail to Hold a Significant Share.

Keywords for candidate selection.

The Report Covers India's Big Data Services Market Trends and is Segmented by Type (Solution, Services), Organization Size (Small & Medium Enterprise, Large Enterprise), and End-User Vertical (BFSI, Retail, Telecommunication & IT, Media & Entertainment, Healthcare). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

[Keywords] Market include MAPR Technologies, Qubole, Amazon Web Services (AWS), Datasift, Hitachi Data Systems

[Keywords] Market include Oracle Corporation, Qlik Technologies Inc., Retail Next Inc., Prevedere Software Inc., Zap Business Intelligence

Comprehensively analyzes and provides civil complaint data collected from the National Petition Center and local government civil complaint windows. You can view data such as rapidly increasing keyword information, core keyword information, civil complaint analysis classification system information, customized statistical information, keyword trend information, similar case information, related word analysis information, today's civil complaint issues, ranking of civil complaint-generating organizations, ranking of civil complaint-generating regions, keyword-based civil complaint volume information, civil complaint status information compared to regional population, most-complaint keyword information, analysis report information, keyword-based gender information, and keyword-based age information. Through this, you can identify the types and trends of civil complaints and utilize them to establish policies and improve administrative services.

The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature review to (a) portray current evidence and knowledge gaps in self-proclaimed undergraduate data science education research and (b) inform policymakers and the data science education community about what educators may encounter when searching for literature using the general keyword “data science education.” While open-access publications that target a broader audience of data science educators and include multiple examples of data science programs and courses are a strength, substantial knowledge gaps remain. The undergraduate data science literature that we identified often lacks empirical data, research questions, and reproducibility. Certain disciplines are less visible. We recommend that we should (a) cherish data science as an interdisciplinary field; (b) adopt a consistent set of keywords/terminology to ensure data science education literature is easily identifiable; (c) prioritize investments in empirical studies.

The Cognitive Data Management market is experiencing robust growth, projected to reach a significant size by 2033, driven by a Compound Annual Growth Rate (CAGR) of 21.70% from 2025 to 2033. This expansion is fueled by several key factors. The increasing volume and complexity of data generated across various industries necessitate sophisticated management solutions capable of handling unstructured and semi-structured data sources. The rise of artificial intelligence (AI) and machine learning (ML) further accelerates adoption, as these technologies require efficient and intelligent data management for optimal performance. Furthermore, the growing demand for data-driven decision-making across sectors like BFSI (Banking, Financial Services, and Insurance), healthcare, and manufacturing is propelling market growth. Cloud-based deployment models are gaining traction due to their scalability, cost-effectiveness, and ease of access. However, challenges remain, including the complexity of integrating cognitive technologies into existing IT infrastructure, concerns regarding data security and privacy, and the need for skilled professionals to manage and interpret insights derived from cognitive data management systems. The market is highly competitive, with established players like SAS Institute, IBM, and Informatica alongside emerging technology companies constantly innovating to provide advanced solutions. The segmentation of the market reveals strong growth across various components, including solutions and services, deployment types (on-premises and cloud), and industry verticals. While the North American market currently holds a significant share, the Asia-Pacific region is poised for rapid expansion due to increasing digitalization and technological adoption. The competitive landscape is dynamic, characterized by strategic partnerships, mergers and acquisitions, and continuous product innovation. Companies are focusing on enhancing their platforms' AI capabilities, improving data integration functionalities, and expanding their cloud offerings to cater to the evolving needs of diverse industries. The overall outlook for the Cognitive Data Management market remains positive, with significant growth opportunities anticipated throughout the forecast period. This comprehensive report provides a detailed analysis of the Cognitive Data Management market, offering invaluable insights for businesses seeking to navigate this rapidly evolving landscape. The study period covers 2019-2033, with 2025 serving as the base and estimated year, and a forecast period spanning 2025-2033. This in-depth analysis encompasses market size, segmentation, growth drivers, challenges, and future trends, offering a 360-degree view of this multi-billion dollar industry. Key market players such as SAS Institute Inc, Infosys Limited, Wipro Limited, Cognizant, IBM Corporation, and many others are profiled, providing a competitive landscape overview. The report utilizes high-search-volume keywords like "cognitive data management," "AI-powered data management," "big data analytics," "cloud-based data management," and "predictive analytics" to enhance search engine visibility. Key drivers for this market are: , Growth in IoT Based Devices increasing the Amount of Digital Data; Increased Adoption of Advanced Analytics and Cognitive Computing Technology. Potential restraints include: , Complex Analytical Processes; Existing Data Security Apprehensions. Notable trends are: IT and Telecommunication Segment to Grow Significantly.

The System of Insight industry is experiencing robust growth, driven by increasing demand for data-driven decision-making across various sectors. The period from 2019 to 2024 witnessed significant expansion, laying a strong foundation for continued growth throughout the forecast period (2025-2033). While the exact market size for 2025 is not provided, considering a conservative estimate based on historical trends and the current market dynamics, a reasonable assumption is that the market value sits around $15 billion USD. This figure is influenced by the rising adoption of advanced analytics, artificial intelligence (AI), and machine learning (ML) technologies within organizations seeking to improve operational efficiency, enhance customer experiences, and gain a competitive edge. The integration of these technologies allows businesses to extract actionable insights from vast datasets, leading to more informed strategic choices and improved business outcomes. Further fueling this growth are increasing investments in data infrastructure and the growing availability of skilled professionals capable of harnessing the power of these sophisticated analytical tools. Looking ahead to 2033, the industry is projected to maintain a healthy Compound Annual Growth Rate (CAGR), let's assume a conservative CAGR of 12%. This signifies substantial market expansion, with significant contributions anticipated from emerging markets and the widespread adoption of cloud-based analytics platforms. The continued development and refinement of AI and ML algorithms, coupled with decreasing data storage and processing costs, will further accelerate growth. The focus is shifting towards real-time analytics and predictive modeling, enabling businesses to respond proactively to market changes and customer needs, creating new avenues for industry expansion. The industry’s future hinges on the successful integration of these advanced technologies and the ability to effectively address the challenges associated with data security and privacy. This comprehensive report provides an in-depth analysis of the rapidly evolving System of Insight industry, offering invaluable insights for businesses seeking to leverage data-driven decision-making. We delve into market dynamics, growth drivers, and competitive landscapes, covering the period from 2019 to 2033, with a base year of 2025 and a forecast period spanning 2025-2033. This report utilizes data from the historical period of 2019-2024 to provide a robust foundation for future projections. Keywords include: system of insight, business intelligence, data analytics, predictive analytics, real-time analytics, customer analytics, sales analytics, operational analytics, market intelligence, data visualization, big data analytics, AI-driven analytics. Key drivers for this market are: , Increasing Volume of Big Data and Growing Need of Analytics; Increasing Focus on Real-Time Insights to Gain a Competitive Edge in the Market. Potential restraints include: , Lack of Integration With Legacy Architecture; Increasing Market Competition. Notable trends are: Retail and e-Commerce Segment to Grow Significantly.

With the 2025 Civil Complaint Big Data Analysis API, you can search for the number of civil complaints by institution based on keywords and the legal information based on keywords, so you can understand the civil complaint processing of the institution based on keywords, check the legal information, and use it to improve practical administrative services. In addition, it can be used in various fields in the public and private sectors by providing the information necessary for research or analysis based on civil complaint data.

Additional file 1. Dataset used in this study.

The global Online Analytical Processing (OLAP) tools market is experiencing robust growth, driven by the increasing demand for data-driven decision-making across various industries. The market, currently estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This significant expansion is fueled by several key factors. The widespread adoption of cloud-based OLAP solutions offers scalability, cost-effectiveness, and accessibility, attracting both large enterprises and SMEs. Furthermore, the rising volume and complexity of data necessitate sophisticated analytical tools for effective data mining and business intelligence. The emergence of advanced analytics capabilities, such as predictive modeling and machine learning integration within OLAP platforms, further enhances their value proposition. The expanding adoption of big data technologies and the growing need for real-time business insights are also contributing to the market's growth trajectory. However, the market faces some challenges. High implementation costs, especially for on-premises solutions, can hinder adoption, particularly among smaller businesses. The complexity of integrating OLAP tools with existing IT infrastructure can also pose a barrier. Additionally, the need for skilled professionals to effectively utilize and manage OLAP systems creates a talent gap that could impact market growth. Despite these constraints, the long-term outlook for the OLAP tools market remains positive, driven by ongoing technological advancements, increasing data volumes, and the persistent need for data-driven decision-making across sectors. The market's segmentation by deployment type (cloud-based vs. on-premises) and user type (large enterprises vs. SMEs) highlights diverse growth opportunities for vendors specializing in specific segments. This comprehensive report provides an in-depth analysis of the global Online Analytical Processing (OLAP) tools market, projecting a value of approximately $15 billion by 2025. We examine market concentration, key trends, dominant segments, product insights, and future growth catalysts. This report is crucial for businesses seeking to understand this rapidly evolving landscape and make informed strategic decisions. Keywords: OLAP, Online Analytical Processing, Business Intelligence, Data Analytics, Data Visualization, Cloud-Based BI, On-Premise BI, Big Data Analytics, Data Warehousing.

Baidu Search Index is a big data analytics tool developed by Baidu to track changes in keyword search popularity within its search engine. By analyzing trends in the Baidu Search Index for specific keywords, users can effectively monitor public interest in topics, companies, or brands.

As an ecosystem partner of Baidu Index, Datago has direct access to keyword search index data from Baidu's database, leveraging this information to build the BSIA-Consumer. This database encompasses popular brands that are actively searched by Chinese consumers, along with their commonly used names. By tracking Baidu Index search trends for these keywords, Datago precisely maps them to their corresponding publicly listed stocks.

The database covers over 1,100 consumer stocks and 3,000+ brand keywords across China, the United States, Europe, and Japan, with a particular focus on popular sectors like luxury goods and vehicles. Through its analysis of Chinese consumer search interest, this database offers investors a unique perspective on market sentiment, consumer preferences, and brand influence, including:

• Brand Influence Tracking – By leveraging Baidu Search Index data, investors can assess the level of consumer interest in various brands, helping to evaluate their influence and trends within the Chinese market.

• Consumer Stock Mapping – BSIA-consumer provides an accurate linkage between brand keywords and their associated consumer stocks, enabling investor analysis driven by consumer interest.

• Coverage of Popular Consumer Goods – BSIA-consumer focuses specifically on trending sectors like luxury goods and vehicles, offering valuable insights into these industries.

• Coverage: 1000+ consumer stocks

• History: 2016-01-01

• Update Frequency: Daily

[Keywords] Market include Core Digital Media, Data Plus Math, Catalina Marketing, Gravy Analytics, 4C

The text analytics market is experiencing robust growth, projected to reach $10.49 billion in 2025 and exhibiting a remarkable Compound Annual Growth Rate (CAGR) of 39.90% from 2019 to 2033. This expansion is fueled by several key drivers. The increasing volume of unstructured data generated across various industries, including healthcare, finance, and customer service, necessitates sophisticated tools for extracting actionable insights. Furthermore, advancements in natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) are empowering text analytics solutions with enhanced capabilities, such as sentiment analysis, topic modeling, and entity recognition. The rising adoption of cloud-based solutions also contributes to market growth, offering scalability, cost-effectiveness, and ease of access. Major industry players like IBM, Microsoft, and SAP are actively investing in research and development, driving innovation and expanding the market's capabilities. Competitive pressures are fostering a continuous improvement in the accuracy and efficiency of text analytics tools, making them increasingly attractive to businesses of all sizes. The growing demand for real-time insights and improved customer experience further propels market expansion. While the market enjoys significant growth momentum, certain challenges persist. Data security and privacy concerns remain paramount, necessitating robust security measures within text analytics platforms. The complexity of implementing and integrating these solutions into existing IT infrastructures can also pose a barrier to adoption, particularly for smaller businesses lacking dedicated data science teams. Furthermore, the accuracy and reliability of text analytics outputs can be affected by the quality and consistency of the input data. Overcoming these challenges through improved data governance, user-friendly interfaces, and robust customer support will be crucial for continued market expansion. Despite these restraints, the overall market outlook remains positive, driven by the continuous evolution of technology and the growing reliance on data-driven decision-making across diverse sectors. Recent developments include: January 2023- Microsoft announced a new multibillion-dollar investment in ChatGPT maker Open AI. ChatGPT, automatically generates text based on written prompts in a more creative and advanced than the chatbots. Through this investment, the company will accelerate breakthroughs in AI, and both companies will commercialize advanced technologies., November 2022 - Tntra and Invenio have partnered to develop a platform that offers comprehensive data analysis on a firm. Throughout the process, Tntra offered complete engineering support and cooperation to Invenio. Tantra offers feeds, knowledge graphs, intelligent text extraction, and analytics, which enables Invenio to give information on seven parts of the business, such as false news identification, subject categorization, dynamic data extraction, article summaries, sentiment analysis, and keyword extraction.. Key drivers for this market are: Growing Demand for Social Media Analytics, Rising Practice of Predictive Analytics. Potential restraints include: Growing Demand for Social Media Analytics, Rising Practice of Predictive Analytics. Notable trends are: Retail and E-commerce to Hold a Significant Share in Text Analytics Market.

Baidu Search Index is a big data analytics tool developed by Baidu, the most popular search engine in China, to reflect changes in search popularity for specific keywords.

Based on an ecosystem partnership with Baidu Search Index, Datago has direct access to keyword search index data from Baidu Index’s database. BSIA-Investor selects A-share stock codes in different formats as keywords, aggregates the corresponding Baidu Index data, and provides insights into the online search interest of Chinese investors for over 5,000 A-share stocks. This data helps investors better understand the market sentiment of millions of Chinese investors toward A-shares, including:

• Investor Interest Measurement: A direct reflection of how Chinese investors’ interest in the A-share market fluctuates.

• Cross-Comparison of Listed Companies: Search index data offers strong comparability, enabling users to assess differences in market attention among various listed companies and identify high-interest stocks.

• Trend Tracking & Market Insights: By monitoring changes in the search popularity of individual stocks, investors can capture market hotspots, gain timely insights into potential investment opportunities, and leverage data for informed decision-making.

• Coverage: 5000+ A-share stocks

• History: 2016-01-01

• Frequency: Daily