The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027.

What is Big data?

Big data is a term that refers to the kind of data sets that are too large or too complex for traditional data processing applications. It is defined as having one or some of the following characteristics: high volume, high velocity or high variety. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets.

Big data analytics

Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate new business insights. The global big data and business analytics market was valued at 169 billion U.S. dollars in 2018 and is expected to grow to 274 billion U.S. dollars in 2022. As of November 2018, 45 percent of professionals in the market research industry reportedly used big data analytics as a research method.

The global big data and business analytics (BDA) market was valued at 168.8 billion U.S. dollars in 2018 and is forecast to grow to 215.7 billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around 85 billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate 79.4 ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around 16.5 billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.

Big Data Analytics for Clinical Research Market Outlook

As per our latest research, the Big Data Analytics for Clinical Research market size reached USD 7.45 billion globally in 2024, reflecting a robust adoption pace driven by the increasing digitization of healthcare and clinical trial processes. The market is forecasted to grow at a CAGR of 17.2% from 2025 to 2033, reaching an estimated USD 25.54 billion by 2033. This significant growth is primarily attributed to the rising need for real-time data-driven decision-making, the proliferation of electronic health records (EHRs), and the growing emphasis on precision medicine and personalized healthcare solutions. The industry is experiencing rapid technological advancements, making big data analytics a cornerstone in transforming clinical research methodologies and outcomes.

Several key growth factors are propelling the expansion of the Big Data Analytics for Clinical Research market. One of the primary drivers is the exponential increase in clinical data volumes from diverse sources, including EHRs, wearable devices, genomics, and imaging. Healthcare providers and research organizations are leveraging big data analytics to extract actionable insights from these massive datasets, accelerating drug discovery, optimizing clinical trial design, and improving patient outcomes. The integration of artificial intelligence (AI) and machine learning (ML) algorithms with big data platforms has further enhanced the ability to identify patterns, predict patient responses, and streamline the entire research process. These technological advancements are reducing the time and cost associated with clinical research, making it more efficient and effective.

Another significant factor fueling market growth is the increasing collaboration between pharmaceutical & biotechnology companies and technology firms. These partnerships are fostering the development of advanced analytics solutions tailored specifically for clinical research applications. The demand for real-world evidence (RWE) and real-time patient monitoring is rising, particularly in the context of post-market surveillance and regulatory compliance. Big data analytics is enabling stakeholders to gain deeper insights into patient populations, treatment efficacy, and adverse event patterns, thereby supporting evidence-based decision-making. Furthermore, the shift towards decentralized and virtual clinical trials is creating new opportunities for leveraging big data to monitor patient engagement, adherence, and safety remotely.

The regulatory landscape is also evolving to accommodate the growing use of big data analytics in clinical research. Regulatory agencies such as the FDA and EMA are increasingly recognizing the value of data-driven approaches for enhancing the reliability and transparency of clinical trials. This has led to the establishment of guidelines and frameworks that encourage the adoption of big data technologies while ensuring data privacy and security. However, the implementation of stringent data protection regulations, such as GDPR and HIPAA, poses challenges related to data integration, interoperability, and compliance. Despite these challenges, the overall outlook for the Big Data Analytics for Clinical Research market remains highly positive, with sustained investments in digital health infrastructure and analytics capabilities.

From a regional perspective, North America currently dominates the Big Data Analytics for Clinical Research market, accounting for the largest share due to its advanced healthcare infrastructure, high adoption of digital technologies, and strong presence of leading pharmaceutical companies. Europe follows closely, driven by increasing government initiatives to promote health data interoperability and research collaborations. The Asia Pacific region is emerging as a high-growth market, supported by expanding healthcare IT investments, rising clinical trial activities, and growing awareness of data-driven healthcare solutions. Latin America and the Middle East & Africa are also witnessing gradual adoption, albeit at a slower pace, due to infrastructural and regulatory challenges. Overall, the global market is poised for substantial growth across all major regions over the forecast period.

Big Data Analytics In Defense and Aerospace Market Outlook

The global market size for Big Data Analytics in Defense and Aerospace was valued at approximately $7.5 billion in 2023 and is expected to reach around $18.2 billion by 2032, growing at a compound annual growth rate (CAGR) of 10.3% during the forecast period. The primary growth factors for this market include the increasing need for advanced analytics to improve decision-making processes, enhance operational efficiency, and ensure better defense and aviation safety and security.

One of the major growth factors driving the Big Data Analytics in Defense and Aerospace market is the rising adoption of IoT and connected devices within the industry. Smart sensors and IoT devices generate vast amounts of data that can be analyzed to optimize operations, predict maintenance needs, and enhance security measures. This influx of data necessitates advanced analytics solutions capable of processing and deriving actionable insights, thereby boosting market growth.

Another crucial growth driver is the escalating demand for enhanced situational awareness and predictive analytics in defense operations. Leveraging big data analytics, military forces can gain comprehensive situational awareness by integrating data from various sources, such as satellite imagery, radar, and reconnaissance reports. This capability not only improves strategic decision-making but also aids in predicting potential threats and assessing risk levels, thereby significantly enhancing defense preparedness and response strategies.

Additionally, the aerospace sector is increasingly relying on big data analytics to improve operational efficiency and safety. Airlines and aviation companies are utilizing analytics to monitor aircraft performance, predict maintenance requirements, and optimize flight paths. This not only helps in reducing operational costs but also ensures higher safety standards and minimizes the risk of unexpected failures. The trend towards digitization in aviation is further fueling the adoption of big data analytics solutions, thereby propelling market growth.

From a regional perspective, North America is expected to dominate the Big Data Analytics in Defense and Aerospace market due to the presence of major defense contractors, advanced technological infrastructure, and significant investments in R&D activities. However, other regions like Asia Pacific are witnessing rapid growth due to increasing defense budgets and modernization programs, as well as a burgeoning commercial aviation sector. Europe also represents a significant market owing to its strong aerospace industry and substantial government support for technological advancements.

Component Analysis

The component segment of the Big Data Analytics in Defense and Aerospace market is divided into software, hardware, and services. The software segment includes various analytics platforms and tools used for data processing, visualization, and predictive analytics. The increasing complexity of data and the need for real-time analytics are driving the demand for sophisticated software solutions. Moreover, advancements in artificial intelligence and machine learning are further enhancing the capabilities of analytics software, making it a critical component of the market.

Hardware, another critical component, encompasses data storage devices, processors, and networking equipment necessary to support big data analytics infrastructure. The growing volumes of data generated by defense and aerospace operations necessitate robust and scalable hardware solutions. Innovations in storage technologies, such as solid-state drives (SSDs) and high-performance computing (HPC) systems, are significantly contributing to the market growth by providing faster data processing and retrieval capabilities.

The services segment includes consulting, implementation, and maintenance services that are essential for the effective deployment and operation of big data analytics solutions. As organizations within the defense and aerospace sectors increasingly adopt these technologies, the demand for specialized services to ensure seamless integration, optimal performance, and continuous support is rising. Service providers play a crucial role in helping organizations navigate the complexities of big data analytics, thereby driving market expansion.

In conclusion, each component of big data analytics—software, hardware, and services—plays a vital role in the overall market ecosystem. The interdependence of these components e

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Big Data Services Market Size 2025-2029

The big data services market size is forecast to increase by USD 604.2 billion, at a CAGR of 54.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of big data in various industries, particularly in blockchain technology. The ability to process and analyze vast amounts of data in real-time is revolutionizing business operations and decision-making processes. However, this market is not without challenges. One of the most pressing issues is the need to cater to diverse client requirements, each with unique data needs and expectations. This necessitates customized solutions and a deep understanding of various industries and their data requirements. Additionally, ensuring data security and privacy in an increasingly interconnected world poses a significant challenge. Companies must navigate these obstacles while maintaining compliance with regulations and adhering to ethical data handling practices. To capitalize on the opportunities presented by the market, organizations must focus on developing innovative solutions that address these challenges while delivering value to their clients. By staying abreast of industry trends and investing in advanced technologies, they can effectively meet client demands and differentiate themselves in a competitive landscape.

What will be the Size of the Big Data Services Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by the ever-increasing volume, velocity, and variety of data being generated across various sectors. Data extraction is a crucial component of this dynamic landscape, enabling entities to derive valuable insights from their data. Human resource management, for instance, benefits from data-driven decision making, operational efficiency, and data enrichment. Batch processing and data integration are essential for data warehousing and data pipeline management. Data governance and data federation ensure data accessibility, quality, and security. Data lineage and data monetization facilitate data sharing and collaboration, while data discovery and data mining uncover hidden patterns and trends. Real-time analytics and risk management provide operational agility and help mitigate potential threats. Machine learning and deep learning algorithms enable predictive analytics, enhancing business intelligence and customer insights. Data visualization and data transformation facilitate data usability and data loading into NoSQL databases. Government analytics, financial services analytics, supply chain optimization, and manufacturing analytics are just a few applications of big data services. Cloud computing and data streaming further expand the market's reach and capabilities. Data literacy and data collaboration are essential for effective data usage and collaboration. Data security and data cleansing are ongoing concerns, with the market continuously evolving to address these challenges. The integration of natural language processing, computer vision, and fraud detection further enhances the value proposition of big data services. The market's continuous dynamism underscores the importance of data cataloging, metadata management, and data modeling for effective data management and optimization.

How is this Big Data Services Industry segmented?

The big data services industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ComponentSolutionServicesEnd-userBFSITelecomRetailOthersTypeData storage and managementData analytics and visualizationConsulting servicesImplementation and integration servicesSupport and maintenance servicesSectorLarge enterprisesSmall and medium enterprises (SMEs)GeographyNorth AmericaUSMexicoEuropeFranceGermanyItalyUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW).

By Component Insights

The solution segment is estimated to witness significant growth during the forecast period.Big data services have become indispensable for businesses seeking operational efficiency and customer insight. The vast expanse of structured and unstructured data presents an opportunity for organizations to analyze consumer behaviors across multiple channels. Big data solutions facilitate the integration and processing of data from various sources, enabling businesses to gain a deeper understanding of customer sentiment towards their products or services. Data governance ensures data quality and security, while data federation and data lineage provide transparency and traceability. Artificial intelligenc

The Big Data Market size is expected to reach a valuation of USD 703.75 billion in 2033 growing at a CAGR of 13.50%. The Big Data market research report classifies market by share, trend, demand, forecast and based on segmentation.

Big Data And Analytics Market Outlook

The global big data and analytics market size is anticipated to grow from $271.83 billion in 2023 to $655.53 billion by 2032, exhibiting a robust CAGR of 10.3% during the forecast period. This remarkable growth is fueled by the increasing adoption of data-driven decision-making processes and the escalating volume of data generated across various industries. Organizations are increasingly relying on advanced analytics to gain competitive advantages, optimize operations, and enhance customer experiences, driving the market forward.

One of the major growth factors of the big data and analytics market is the exponential rise in data generation. With the proliferation of connected devices, social media interactions, e-commerce transactions, and digital communications, the volume of data being produced is unprecedented. This vast amount of data, often referred to as "big data," presents immense opportunities for organizations to extract valuable insights using sophisticated analytics tools. Furthermore, advancements in data storage and processing technologies have enabled businesses to handle and analyze massive datasets efficiently, further propelling market growth.

Another significant factor contributing to the market's expansion is the increasing emphasis on personalized customer experiences. In today's competitive landscape, businesses are striving to understand customer preferences and behaviors better to deliver tailored products and services. Big data analytics allows organizations to analyze customer data in real time, enabling them to create personalized marketing campaigns, improve customer service, and enhance overall customer satisfaction. This shift towards customer-centric strategies is driving the demand for big data and analytics solutions across various industries, including retail, BFSI, and healthcare.

Additionally, the growing need for operational efficiency and cost optimization is spurring the adoption of big data analytics. Organizations are leveraging analytics to streamline their operations, identify inefficiencies, and make data-driven decisions to optimize resource allocation. For instance, in the manufacturing sector, predictive analytics is being used to improve production processes, minimize downtime, and reduce maintenance costs. Similarly, in the healthcare industry, big data analytics is helping to improve patient outcomes, optimize treatment plans, and reduce healthcare costs. The ability to derive actionable insights from data is becoming a critical factor for businesses aiming to enhance their operational efficiency and overall performance.

The regional outlook for the big data and analytics market indicates significant growth across all major regions. North America currently holds the largest market share, driven by the early adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by the rapid digital transformation, increasing internet penetration, and the growing adoption of big data analytics by businesses in emerging economies such as China and India. Europe is also experiencing steady growth, supported by stringent data protection regulations and the rising demand for data-driven insights.

Component Analysis

The big data and analytics market can be segmented by component into software, hardware, and services. Software solutions dominate this segment, driven by the widespread adoption of advanced analytics tools and platforms. Big data software includes data management solutions, business intelligence tools, machine learning platforms, and predictive analytics applications. These solutions enable organizations to collect, store, process, and analyze vast amounts of data, deriving actionable insights to drive business decisions. The continuous advancements in software capabilities, such as real-time analytics and AI-driven insights, are further fueling the growth of this segment.

Hardware components are also essential for the big data and analytics market, providing the necessary infrastructure to support data processing and storage. This segment encompasses servers, storage systems, and networking equipment. With the increasing volume of data being generated, organizations require robust hardware solutions to handle the processing and storage demands. Innovations in hardware technologies, such as high-performance computing and scalable storage solutions, are enabling businesses to manage and analyze large datasets more efficiently. The demand for ha

The statistic shows the areas in which companies use or plan to use big data analytics worldwide as of 2017. A quarter of respondents stated that their company currently uses big data analytics for marketing, with another 25 percent stating that their business planned to use big data for marketing within the next 12 months.

According to Cognitive Market Research, the global Hadoop big data analytics market size is USD 12.8 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 13.0% from 2024 to 2031. Market Dynamics of Hadoop Big Data Analytics Market Key Drivers for Hadoop Big Data Analytics Market Increasing the use of internet transactions- The market for Hadoop big data analytics is expanding because more and more transactions are being made online. Digital financial transactions are any monetary transfers that take place through digital devices or internet-based sites. The huge amounts of data created throughout interactions are processed, managed, and analyzed in an effective and accessible manner using Hadoop and large-scale analytics, which are also used in online payments to improve speed, safety, and customization of payment options. As a result, the Hadoop big data analytics industry is expanding due to the growing use of online payments. The global pharmaceutical industry's adoption of Hadoop big data analytics is driving the industry's expansion. Key Restraints for Hadoop Big Data Analytics Market The growing internet risk is the main factor impeding the worldwide Hadoop Big Data Analytics industry's expansion. Inadequate recognition in low-income nations is also hampering the market growth. Introduction of the Hadoop Big Data Analytics Market Hadoop big data analytics is the practice of utilizing the Hadoop computing system to examine massive amounts of data in all its forms. Hadoop is an operating system for storing, processing, and evaluating large amounts of diverse data used for large-scale processing that is portable, inexpensive, and flexible. Because of its capacity to effectively manage and evaluate massive amounts of statistics, it is utilized for an extensive number of applications in a variety of businesses and areas. The goal of this technique is to help various businesses stay competing in the demand and obtain more information about the business sector. The need for a single, standardized infrastructure for maintaining data will support the expansion of the Hadoop big data analytics market.

Storage in Big Data Market Outlook

The global storage in big data market size was estimated to be USD 57.5 billion in 2023, and it is projected to reach approximately USD 147.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.0% during the forecast period. This growth can be attributed to the increasing volume of data generated by various industry verticals, advancements in data storage technologies, and the rising adoption of big data analytics across organizations worldwide. The rapid digital transformation across industries has necessitated efficient data storage solutions, paving the way for substantial growth in the big data storage market.

The proliferation of data generated from various sources such as social media, IoT devices, and enterprise applications is one of the major growth factors for the storage in big data market. The exponential increase in data volume has created a pressing need for effective storage solutions that can handle, manage, and analyze large datasets in real time. Organizations are increasingly relying on data-driven insights to inform their business strategies, optimize operations, and enhance customer experiences, thereby driving the demand for sophisticated storage solutions. Furthermore, the growing importance of data in decision-making processes has underscored the critical role of robust storage infrastructure to support big data initiatives.

Technological advancements in storage solutions, such as the development of high-performance storage systems and cloud-based storage platforms, have significantly contributed to the market's growth. Innovations in storage technologies, including the use of solid-state drives (SSDs), non-volatile memory express (NVMe), and software-defined storage (SDS), have enhanced storage efficiency and accessibility, meeting the demands of organizations dealing with massive data volumes. Additionally, cloud-based storage solutions have gained traction due to their scalability, flexibility, and cost-effectiveness, enabling businesses to manage their data resources more efficiently. These technological advancements are expected to drive the adoption of big data storage solutions over the forecast period.

The increasing investment in big data analytics by various industries is another key growth driver for the storage in big data market. Industries such as healthcare, retail, BFSI (banking, financial services, and insurance), and IT and telecommunications are leveraging big data analytics to derive valuable insights from their data reserves. As a result, there is a growing demand for advanced storage solutions capable of supporting complex data analytics processes. The integration of machine learning and artificial intelligence with big data analytics further emphasizes the need for efficient storage systems that can handle the processing of large datasets, thereby boosting the market growth.

The regional outlook for the storage in big data market indicates that North America is expected to hold a significant share of the market during the forecast period. This dominance can be attributed to the early adoption of advanced technologies, the presence of major market players, and the high investment in big data analytics in the region. Additionally, the Asia Pacific region is projected to witness the highest growth rate, driven by the increasing adoption of digital technologies, the expansion of the IT sector, and the growing focus on data-driven decision-making processes. Europe is also anticipated to experience substantial growth, supported by the rising demand for data storage solutions across various industries and increasing regulatory requirements for data management.

Component Analysis

The component segment of the storage in big data market is divided into hardware, software, and services. Each component plays a critical role in the overall market ecosystem and contributes to the effective management and utilization of big data. Hardware components, which include storage devices and infrastructure, are essential for storing the vast amounts of data generated by organizations. With advancements in storage technologies, hardware components have evolved to offer higher storage capacities, faster data retrieval speeds, and better energy efficiency. Innovations such as SSDs and NVMe have revolutionized the storage landscape, providing organizations with robust solutions to meet their growing data storage needs.

Software components in the big data storage market are designed to enhance the functionality and management of stored data. They include data management software, data in

The Hadoop As-A-Service segment will retain its strong market share due to its open-source nature, scalability, and widespread adoption. Data As-A-Service will continue to grow rapidly, as businesses seek pre-processed data tailored to specific use cases. Data Analytics As-A-Service is gaining traction, as companies increasingly leverage cloud-based analytics platforms to drive data-driven decision-making. Notable trends are: Increasing usage of social platforms boosts market growth globally..

This graph presents the results of a survey, conducted by BARC in 2014/15, into the current and planned use of technology for the analysis of big data. At the beginning of 2015, 13 percent of respondents indicated that their company was already using a big data analytical appliance for big data.

According to Cognitive Market Research, the global SME Big Data market size is USD xx million in 2024. It will expand at a compound annual growth rate (CAGR) of 4.60% from 2024 to 2031. North America held the major market share for more than 40% of the global revenue with a market size of USD xx million in 2024 and will grow at a compound annual growth rate (CAGR) of 2.8% from 2024 to 2031. Europe accounted for a market share of over 30% of the global revenue with a market size of USD xx million. Asia Pacific held a market share of around 23% of the global revenue with a market size of USD xx million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.6% from 2024 to 2031. Latin America had a market share for more than 5% of the global revenue with a market size of USD xx million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.0% from 2024 to 2031. Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD xx million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.3% from 2024 to 2031. The Software held the highest SME Big Data market revenue share in 2024. Market Dynamics of SME Big Data Market Key Drivers for SME Big Data Market Growing Recognition of Data-Driven Decision Making The growing recognition of data-driven decision making is a key driver in the SME Big Data market as businesses increasingly understand the value of leveraging data for strategic decisions. This shift enables SMEs to optimize operations, enhance customer experiences, and gain competitive advantages. Access to affordable big data technologies and analytics tools has democratized data usage, making it feasible for smaller enterprises to adopt these solutions. SMEs can now analyze market trends, customer behaviors, and operational inefficiencies, leading to more informed and agile business strategies. This recognition propels demand for big data solutions, as SMEs seek to harness data insights to improve outcomes, innovate, and stay competitive in a rapidly evolving business landscape. Growing Number of Affordable Big Data Solutions The growing number of affordable big data solutions is driving the SME Big Data market by lowering the entry barrier for smaller enterprises to adopt advanced analytics. Cost-effective technologies, particularly cloud-based services, allow SMEs to access powerful data analytics tools without substantial upfront investments in infrastructure. This affordability enables SMEs to harness big data to gain insights into customer behavior, streamline operations, and enhance decision-making processes. As a result, more SMEs are integrating big data into their business models, leading to improved efficiency, innovation, and competitiveness. The availability of scalable and flexible solutions tailored to SME needs further accelerates adoption, making big data analytics an accessible and valuable resource for small and medium-sized businesses aiming for growth and success. Restraint Factor for the SME Big Data Market High Initial Investment Cost to Limit the Sales High initial costs are a significant restraint on the SME Big Data market, as they can deter smaller businesses from adopting big data technologies. Implementing big data solutions often requires substantial investment in hardware, software, and skilled personnel, which can be prohibitively expensive for SMEs with limited budgets. These costs include purchasing or subscribing to analytics platforms, upgrading IT infrastructure, and hiring data scientists or analysts. The financial burden associated with these initial expenses can make SMEs hesitant to commit to big data projects, despite the potential long-term benefits. Consequently, high initial costs limit the accessibility of big data analytics for SMEs, slowing the market's overall growth and the widespread adoption of these transformative technologies among smaller enterprises. Impact of Covid-19 on the SME Big Data Market The COVID-19 pandemic significantly impacted the SME Big Data market, accelerating digital transformation as businesses sought to adapt to rapidly changing conditions. With disruptions in traditional operations and a shift towards remote work, SMEs increasingly turned to big data analytics to maintain efficiency, manage supply chains, and understand evolving customer behaviors. The pandemic underscored the importance of real-time data insights for agile decision-making, dr...

The Healthcare Big Data Analytics Market is segmented into the following products:HardwareSoftwareServicesThe hardware segment includes the servers, storage devices, and networking equipment that are used to store and process big data. The software segment includes the software applications that are used to analyze big data. The services segment includes the consulting, implementation, and support services that are needed to deploy and use big data analytics solutions. Recent developments include: March 2022 The government of Thailand launched a big data portal for healthcare facilities. The National Reforms Committee on Public Health recently joined hands with 12 government agencies to improve the quality of healthcare services by implementing digital technologies.. Notable trends are: EHR adoption is increasing in both developing and developed countries to boost the market growth.

The USDA Agricultural Research Service (ARS) recently established SCINet , which consists of a shared high performance computing resource, Ceres, and the dedicated high-speed Internet2 network used to access Ceres. Current and potential SCINet users are using and generating very large datasets so SCINet needs to be provisioned with adequate data storage for their active computing. It is not designed to hold data beyond active research phases. At the same time, the National Agricultural Library has been developing the Ag Data Commons, a research data catalog and repository designed for public data release and professional data curation. Ag Data Commons needs to anticipate the size and nature of data it will be tasked with handling. The ARS Web-enabled Databases Working Group, organized under the SCINet initiative, conducted a study to establish baseline data storage needs and practices, and to make projections that could inform future infrastructure design, purchases, and policies. The SCINet Web-enabled Databases Working Group helped develop the survey which is the basis for an internal report. While the report was for internal use, the survey and resulting data may be generally useful and are being released publicly. From October 24 to November 8, 2016 we administered a 17-question survey (Appendix A) by emailing a Survey Monkey link to all ARS Research Leaders, intending to cover data storage needs of all 1,675 SY (Category 1 and Category 4) scientists. We designed the survey to accommodate either individual researcher responses or group responses. Research Leaders could decide, based on their unit's practices or their management preferences, whether to delegate response to a data management expert in their unit, to all members of their unit, or to themselves collate responses from their unit before reporting in the survey.
Larger storage ranges cover vastly different amounts of data so the implications here could be significant depending on whether the true amount is at the lower or higher end of the range. Therefore, we requested more detail from "Big Data users," those 47 respondents who indicated they had more than 10 to 100 TB or over 100 TB total current data (Q5). All other respondents are called "Small Data users." Because not all of these follow-up requests were successful, we used actual follow-up responses to estimate likely responses for those who did not respond. We defined active data as data that would be used within the next six months. All other data would be considered inactive, or archival. To calculate per person storage needs we used the high end of the reported range divided by 1 for an individual response, or by G, the number of individuals in a group response. For Big Data users we used the actual reported values or estimated likely values.

Resources in this dataset:Resource Title: Appendix A: ARS data storage survey questions. File Name: Appendix A.pdfResource Description: The full list of questions asked with the possible responses. The survey was not administered using this PDF but the PDF was generated directly from the administered survey using the Print option under Design Survey. Asterisked questions were required. A list of Research Units and their associated codes was provided in a drop down not shown here. Resource Software Recommended: Adobe Acrobat,url: https://get.adobe.com/reader/ Resource Title: CSV of Responses from ARS Researcher Data Storage Survey. File Name: Machine-readable survey response data.csvResource Description: CSV file includes raw responses from the administered survey, as downloaded unfiltered from Survey Monkey, including incomplete responses. Also includes additional classification and calculations to support analysis. Individual email addresses and IP addresses have been removed. This information is that same data as in the Excel spreadsheet (also provided).Resource Title: Responses from ARS Researcher Data Storage Survey. File Name: Data Storage Survey Data for public release.xlsxResource Description: MS Excel worksheet that Includes raw responses from the administered survey, as downloaded unfiltered from Survey Monkey, including incomplete responses. Also includes additional classification and calculations to support analysis. Individual email addresses and IP addresses have been removed.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel

Big Data Analytics Market Outlook 2032

The global big data analytics market size was USD 307.44 Billion in 2023 and is likely to reach USD 930.94 Billion by 2032, expanding at a CAGR of 13.1 % during 2024–2032. The market growth is attributed to the increasing need for customer analytics and the rising demand for data-driven decision-making.



Increasing demand for data-driven decision-making is propelling the growth of the big data analytics market. Businesses across various sectors are leveraging this technology to gain insights from vast amounts of data. This technology helps organizations to understand their customers better, improve their products and services, and make informed strategic decisions, as a result, the adoption of big data analytics is on the rise, with companies investing heavily in this technology to stay competitive in the market.

Big data analytics solutions are widely used in the BFSI, automotive, telecom/media, healthcare, life sciences, retail energy & utility, government, and other industries as these solutions help companies predict future trends and consumer behavior, allowing them to meet customer needs effectively and stay ahead of the competition. Additionally, these solutions identify inefficiencies in business processes and suggest improvements, leading to significantly improved productivity and cost savings. These benefits associated with big data analytics encourage industries to adopt these solutions.

Impact of Artificial Intelligence (AI) in Big Data Analytics Market

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Big Data Security Market size was valued at USD 36.57 Billion in 2024 and is projected to reach USD 121.03 Billion by 2031, growing at a CAGR of 17.8% from 2024 to 2031.Global Big Data Security Market DriversGrowth in Data Volumes: Every day, an exponential amount of data is generated from a variety of sources, such as social media, IoT devices, and enterprise applications. For enterprises, managing and safeguarding this enormous volume of data is turning into a major concern. Robust big data security solutions are in high demand due to the requirement to protect important and sensitive data.Growing Complexity of Cyberthreats: Cyberattacks are become more advanced and focused. AI and machine learning are examples of cutting-edge tactics that attackers are employing to get past security measures. Advanced big data security procedures that can recognize, stop, and react to these complex threats instantly are required due to the constantly changing threat landscape.Strict Adherence to Regulations: Strict data protection laws, like the California Consumer Privacy Act (CCPA) in the US and the General Data Protection Regulation (GDPR) in Europe, are being implemented by governments and regulatory agencies around the globe. To avoid heavy fines and legal ramifications, organizations must abide by these requirements. Adoption of comprehensive big data security solutions to guarantee data privacy and protection is being driven by compliance requirements.Cloud Service Proliferation: Cloud services are becoming more and more popular as businesses look for scalable and affordable ways to handle and store data. But moving to cloud settings also means dealing with security issues. The need for big data security solutions that can safeguard cloud-based data is fueled by the need for specific security procedures to protect data in cloud infrastructures.

The Data Analytics Market size was valued at USD 41.05 USD billion in 2023 and is projected to reach USD 222.39 USD billion by 2032, exhibiting a CAGR of 27.3 % during the forecast period. Data Analytics can be defined as the rigorous process of using tools and techniques within a computational framework to analyze various forms of data for the purpose of decision-making by the concerned organization. This is used in almost all fields such as health, money matters, product promotion, and transportation in order to manage businesses, foresee upcoming events, and improve customers’ satisfaction. Some of the principal forms of data analytics include descriptive, diagnostic, prognostic, as well as prescriptive analytics. Data gathering, data manipulation, analysis, and data representation are the major subtopics under this area. There are a lot of advantages of data analytics, and some of the most prominent include better decision making, productivity, and saving costs, as well as the identification of relationships and trends that people could be unaware of. The recent trends identified in the market include the use of AI and ML technologies and their applications, the use of big data, increased focus on real-time data processing, and concerns for data privacy. These developments are shaping and propelling the advancement and proliferation of data analysis functions and uses. Key drivers for this market are: Rising Demand for Edge Computing Likely to Boost Market Growth. Potential restraints include: Data Security Concerns to Impede the Market Progress . Notable trends are: Metadata-Driven Data Fabric Solutions to Expand Market Growth.

Business Analytics Market was valued at USD 84.42 Billion in 2024 and is projected to reach USD 176.14 Billion by 2031, growing at a CAGR of 9.63% from 2024 to 2031.

Global Business Analytics Market Drivers

The market drivers for the Business Analytics Market can be influenced by various factors. These may include:

Growing Adoption of Big Data Analytics: In order to extract meaningful insights from their data, organizations are progressively using big data analytics in response to the exponential expansion of data. Making educated decisions through data analysis is facilitated by business analytics. Growing Need for Data-driven Decision Making: In order to obtain a competitive edge, businesses are realizing the significance of data-driven decision making. The methods and instruments for data analysis and significant insights extraction for improved decision-making are offered by business analytics. Growing Need for Predictive and Prescriptive Analytics: Predictive and prescriptive analytics are becoming more and more in demand as a means of projecting future trends and results. Businesses can use business analytics to prescribe activities to achieve desired outcomes and forecast future outcomes based on previous data. Growing Emphasis on Customer Analytics: As e-commerce and digital marketing gain traction, companies are putting more of an emphasis on comprehending the behavior and preferences of their customers. In order to increase consumer engagement and personalize marketing efforts, business analytics is used to analyze customer data. Emergence of Advanced Technologies: The use of advanced analytics solutions is being propelled by developments in fields like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Businesses may now analyze data more effectively and gain deeper insights thanks to these technologies. Operational Efficiency and Cost Optimization Are Necessary: Companies are always under pressure to increase operational efficiency and reduce costs. Business analytics promotes market expansion by assisting in the identification of opportunities for process and cost-cutting enhancements. Compliance and Regulatory Requirements: The use of business analytics solutions for risk management and compliance reporting is being fueled by the growing regulatory requirements in a number of industries, including healthcare, banking, and retail.

In 2023, around 74.9 percent of companies that used big data analysis and related services in South Korea did so with public data. Following this was the analysis of customer information, at around 42.3 percent.