Journal of Big Data Impact Factor 2023-2024 - ResearchHelpDesk - The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material. All articles published by the Journal of Big Data are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. As authors of articles published in the Journal of Big Data you are the copyright holders of your article and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate your article, according to the SpringerOpen copyright and license agreement. For those of you who are US government employees or are prevented from being copyright holders for similar reasons, SpringerOpen can accommodate non-standard copyright lines.

The Report Covers Global Big Data Analytics in Healthcare Market Trends and is Segmented by Component (Software and Services), Deployment (On-premise and Cloud-based), Application (Financial Analytics, Clinical Data Analytics, Operational Analytics, and Population Health Analytics), and Geography (North America, Europe, Asia-Pacific, Middle East, and Africa, and South America). The value is provided (in USD million) for the above-mentioned segments.

This statistic displays the adoption rates of Big Data analytics in the United Kingdom (UK) in 2015 and 2020. In 2015, the adoption rate amounted to 56 percent across all examined industry. 67 percent of the industries will adopt Big Data analytics in 2020.

The statistic shows the problems that organizations face when using big data technologies worldwide as of 2017. Around 53 percent of respondents stated that inadequate analytical know-how was a major problem that their organization faced when using big data technologies as of 2017.

This is the historic impact factors of Big Data Analytics computed for each year in CSV format. The first column shows the exaly JournalID for mixing this table with those of other journals

Big Data Analytics In Healthcare Market size is estimated at USD 29.30 Billion in 2023 and is projected to reach USD 59.34 Billion by 2031, growing at a CAGR of 9.1% from 2024 to 2031.

Key Market Drivers
Exponential Growth of Healthcare Data: The amount of data generated in healthcare is exploding. This includes electronic health records (EHRs), medical imaging, wearable devices, and even social media data. Immense potential for improving healthcare is held by this vast dataset if it can be analyzed effectively. The tools to unlock these valuable insights are provided by big data analytics.
Rising Demand for Value-Based Care: Value-based care models, which emphasize quality outcomes and cost-efficiency, are increasingly being shifted toward healthcare systems. Healthcare providers are empowered by big data analytics to optimize resource allocation, identify high-risk patients, and develop preventive care strategies. Better patient care and reduced costs are translated to by this, aligning perfectly with value-based care goals.
Regulatory Requirements and Public Health Initiatives: Regulations mandating healthcare data collection and analysis for better disease surveillance, outbreak prevention, and population health management are being implemented by governments across the globe. Big data analytics plays a crucial role in fulfilling these requirements by enabling real-time data analysis and informed decision-making for public health officials.
Advancements in Technology and Infrastructure: The continuous development of big data technologies like cloud computing, artificial intelligence, and machine learning is making data analysis faster, more efficient, and more affordable. This allows big data analytics solutions to be leveraged more readily by healthcare organizations, fueling market growth.

The global big data in healthcare market size was valued at USD 32.9 billion in 2021 and is predicted to reach USD 105.73 billion by 2030, increasing at a CAGR of 13.85% from 2022 to 2030. Big Data in healthcare is the difficult process of ana Report Scope:

Big Data and Society Acceptance Rate - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

The United States healthcare big data analytics market size reached US$ 19.9 Billion in 2023, Expected to Hit US$ 55.8 Billion, CAGR of 11.8% during 2024-2032.

The statistic shows the success rate of various big data initiatives as of 2019, according to a survey of industry-leading firms, primarily in the United States. As of that time, 59.5 percent of respondents reported having seen measurable results from big data initiatives to decrease expenses.

Global Big Data Analytics In Aerospace And Defense Market Size By Type (Apps And Analytics, Professional Services, Infrastructure Software), By Application (Aerospace and Defense), By Geographic Scope And Forecast

The global big data market in the automotive industry size was valued at USD 4,500 million in 2021. It is estimated to reach USD 15,800 million by 2030, growing at a CAGR of 17% during the forecast period (2022–2030). Adopting technology, appl Report Scope:

We introduce a benchmark of distributed algorithms execution over big data. The datasets are composed of metrics about the computational impact (resource usage) of eleven well-known machine learning techniques on a real computational cluster regarding system resource agnostic indicators: CPU consumption, memory usage, operating system processes load, net traffic, and I/O operations. The metrics were collected every five seconds for each algorithm on five different data volume scales, totaling 275 distinct datasets. The tested scenarios embraced problems of regression, clustering, classification, dimensionality reduction, and collaborative filtering. We performed experiments on 2.15 TB of synthetic data produced with Intel HiBench, in a cluster composed of 128 cores and 848 GB RAM managed by Apache Spark framework. We hope these datasets can be used by the scientific community to obtain insights about running algorithms on big data processing platforms.

This statistic shows big data technology adoption plans in organizations worldwide from 2015 to 2019. Around 53 percent of respondents stated that their organization currently used big data technologies as of 2019.

The global AI and Big Data in Food Industry Market size is expected to reach USD 269.92 Billion in 2032 registering a CAGR of 44.4%. Our report provides a comprehensive overview of the industry, including key players, market share, growth opportunities and more.

The big data security market is projected to be valued at US$ 20,418.4 million in 2023 and is expected to rise to US$ 72,652.6 million by 2033. The sales of big data security are expected to record a significant CAGR of 13.5% during the forecast period.

Scope of the Report

The last 40 years have seen huge innovations in computing and in the availability of data. Data derived from millions of administrative records or by using (as we do) new methods of data generation such as text mining are now common. New data often requires new methods, which in turn can inspire new data collection. If history is any guide, some methods will stick and others will prove to be a flash in the pan. However, the larger trends toward demanding greater credibility and transparency from researchers in applied economics and a 'collage' approach to assembling evidence will likely continue.