[Coursera] Web Intelligence and Big Data by Dr. Gautam Shroff

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Big Data Market Size 2025-2029

The big data market size is forecast to increase by USD 193.2 billion at a CAGR of 13.3% between 2024 and 2029.

The market is experiencing a significant rise due to the increasing volume of data being generated across industries. This data deluge is driving the need for advanced analytics and processing capabilities to gain valuable insights and make informed business decisions. A notable trend in this market is the rising adoption of blockchain solutions to enhance big data implementation. Blockchain's decentralized and secure nature offers an effective solution to address data security concerns, a growing challenge in the market. However, the increasing adoption of big data also brings forth new challenges. Data security issues persist as organizations grapple with protecting sensitive information from cyber threats and data breaches.
Companies must navigate these challenges by investing in robust security measures and implementing best practices to mitigate risks and maintain trust with their customers. To capitalize on the market opportunities and stay competitive, businesses must focus on harnessing the power of big data while addressing these challenges effectively. Deep learning frameworks and machine learning algorithms are transforming data science, from data literacy assessments to computer vision models.

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

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In today's data-driven business landscape, the demand for advanced data management solutions continues to grow. Companies are investing in business intelligence dashboards and data analytics tools to gain insights from their data and make informed decisions. However, with this increased reliance on data comes the need for robust data governance policies and regular data compliance audits. Data visualization software enables businesses to effectively communicate complex data insights, while data engineering ensures data is accessible and processed in real-time. Data-driven product development and data architecture are essential for creating agile and responsive business strategies. Data management encompasses data accessibility standards, data privacy policies, and data quality metrics.
Data usability guidelines, prescriptive modeling, and predictive modeling are critical for deriving actionable insights from data. Data integrity checks and data agility assessments are crucial components of a data-driven business strategy. As data becomes an increasingly valuable asset, businesses must prioritize data security and privacy. Prescriptive and predictive modeling, data-driven marketing, and data culture surveys are key trends shaping the future of data-driven businesses. Data engineering, data management, and data accessibility standards are interconnected, with data privacy policies and data compliance audits ensuring regulatory compliance.
Data engineering and data architecture are crucial for ensuring data accessibility and enabling real-time data processing. The data market is dynamic and evolving, with businesses increasingly relying on data to drive growth and inform decision-making. Data engineering, data management, and data analytics tools are essential components of a data-driven business strategy, with trends such as data privacy, data security, and data storytelling shaping the future of data-driven businesses.

How is this Big Data Industry segmented?

The big data 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.

Deployment

  On-premises
  Cloud-based
  Hybrid


Type

  Services
  Software


End-user

  BFSI
  Healthcare
  Retail and e-commerce
  IT and telecom
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

In the realm of big data, on-premise and cloud-based deployment models cater to varying business needs. On-premise deployment allows for complete control over hardware and software, making it an attractive option for some organizations. However, this model comes with a significant upfront investment and ongoing maintenance costs. In contrast, cloud-based deployment offers flexibility and scalability, with service providers handling infrastructure and maintenance. Yet, it introduces potential security risks, as data is accessed through multiple points and stored on external servers. Data

The global big data analytics market size was valued at $307.52 billion in 2023 & is projected to grow from $348.21 billion in 2024 to $961.89 billion by 2032

Question Paper Solutions of chapter Data Base for the Modern Web of Big Data Analysis, 8th Semester , Applied Electronics and Instrumentation Engineering

The Big Data Solutions market is experiencing robust growth, projected to reach a market size of $1007.5 million in 2025. While a precise CAGR isn't provided, considering the rapid advancements in data analytics technologies and the increasing reliance on data-driven decision-making across various sectors, a conservative estimate of the Compound Annual Growth Rate (CAGR) between 2025 and 2033 would be around 15%. This growth is fueled by several key drivers, including the exponential increase in data volume from diverse sources (IoT, social media, etc.), the rising demand for advanced analytics to gain actionable insights, and the increasing adoption of cloud-based big data solutions offering scalability and cost-effectiveness. Government agencies, large enterprises, and small and medium-sized businesses (SMBs) are all significant consumers of big data solutions, driving demand across various application segments. The market is segmented by service models (SaaS, PaaS, IaaS) and end-user applications, allowing vendors to tailor their offerings to specific needs. Key players such as Amazon, Google, Microsoft, IBM, and others are aggressively investing in research and development, fostering innovation and competition within the market. This competitive landscape benefits end-users with improved solutions and cost optimization opportunities. The geographical distribution of the market is diverse, with North America currently holding a significant share, followed by Europe and Asia Pacific. However, the Asia Pacific region is expected to witness the fastest growth rate over the forecast period, driven by increasing digitalization and adoption of advanced technologies in developing economies like India and China. The market faces some restraints, primarily related to the challenges of data security, privacy concerns, and the need for skilled professionals to manage and interpret big data. However, ongoing advancements in data security technologies and the expanding pool of data scientists are mitigating these limitations and supporting continued market expansion. The overall outlook for the Big Data Solutions market is highly positive, with significant opportunities for growth and innovation in the coming years.

This statistic shows the distribution of the global big data market related to healthcare in 2016 and a forecast for 2025, by market share. It is predicted that by 2025 the market share of analytics services will increase to over 42 percent.

WIDEa is R-based software aiming to provide users with a range of functionalities to explore, manage, clean and analyse "big" environmental and (in/ex situ) experimental data. These functionalities are the following, 1. Loading/reading different data types: basic (called normal), temporal, infrared spectra of mid/near region (called IR) with frequency (wavenumber) used as unit (in cm-1); 2. Interactive data visualization from a multitude of graph representations: 2D/3D scatter-plot, box-plot, hist-plot, bar-plot, correlation matrix; 3. Manipulation of variables: concatenation of qualitative variables, transformation of quantitative variables by generic functions in R; 4. Application of mathematical/statistical methods; 5. Creation/management of data (named flag data) considered as atypical; 6. Study of normal distribution model results for different strategies: calibration (checking assumptions on residuals), validation (comparison between measured and fitted values). The model form can be more or less complex: mixed effects, main/interaction effects, weighted residuals.

Over nine percent of organizations in Russia used company websites as the main source for their big data analysis in 2021. A further eight percent opted for business information systems, such as ERP, CRM, SCM, HRIS, and others. Big data stands for large sets of data related to the usage of a good or a service, which allows companies to better understand how products are perceived by end users.

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Big Data Security Market Size 2025-2029

The big data security market size is forecast to increase by USD 23.9 billion, at a CAGR of 15.7% between 2024 and 2029.

The market is driven by stringent regulations mandating data protection and an increasing focus on automation in big data security. With the growing volume and complexity of data, organizations are investing significantly in advanced security solutions to mitigate risks and ensure compliance. However, implementing these solutions comes with high financial requirements, posing a challenge for smaller businesses and budget-constrained organizations. Regulations, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), have intensified the need for robust data security measures. These regulations demand that organizations protect sensitive data from unauthorized access, use, or disclosure.
As a result, companies are investing in big data security solutions that offer advanced encryption, access control, and threat detection capabilities. Another trend in the market is the automation of big data security processes. With the increasing volume and velocity of data, manual security processes are no longer sufficient. Automation helps organizations to respond quickly to threats and maintain continuous security monitoring. However, the high cost of implementing and maintaining these automated solutions can be a significant challenge for many organizations. Intruders, ransomware attacks, unauthorized users, and other threats pose a constant risk to valuable information, intellectual property (IP), and transactional data.

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

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The market continues to evolve, driven by the increasing volume and complexity of data being generated and collected across various sectors. Data governance is a critical aspect of this market, ensuring the secure handling and protection of valuable information. Blue teaming, a collaborative approach to cybersecurity, plays a crucial role in identifying and mitigating threats in real-time. Risk assessment and incident response are ongoing processes that help organizations prepare for and respond to data breaches. Security monitoring, powered by advanced technologies like AI in cybersecurity, plays a vital role in detecting and responding to threats. Data masking and anonymization are essential techniques for protecting sensitive data while maintaining its usability.

Network security, cloud security, and database security are key areas of focus, with ongoing threats requiring continuous vigilance. Threat intelligence and vulnerability management help organizations stay informed about potential risks and prioritize their response efforts. Disaster recovery and business continuity planning are also essential components of a robust security strategy. Cybersecurity insurance, security auditing, access control, penetration testing, and vulnerability scanning are additional services that help organizations fortify their defenses. Zero trust security and application security are emerging areas of focus, reflecting the evolving threat landscape. The market dynamics in this space are continuously unfolding, with new challenges and solutions emerging regularly.

How is this Big Data Security Industry segmented?

The big data security industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud-based


End-user

  Large enterprises
  SMEs


Solution

  Software
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Spain
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Deployment Insights

The On-premises segment is estimated to witness significant growth during the forecast period. The market: Evolution and Trends in Enterprise Computing Big Data Security encompasses a range of technologies and practices designed to protect an organization's valuable data. Traditional on-premises servers form the backbone of many enterprise data infrastructures, with businesses owning and managing their hardware and software. These infrastructures include servers and storage units, located at secure sites, requiring specialized IT support for maintenance. Data security in this context is a top priority. Companies must establish user access policies, install firewalls and antivirus software, and apply security patches promptly. Network security is crucial, with vulnerability management and threat

[Coursera] Web Intelligence and Big Data (Indian Institute of Technology Delhi) (bigdata)

The Big Data User Behavior Analysis Platform market is experiencing robust growth, driven by the increasing need for businesses to understand user interactions and optimize digital experiences. The market, estimated at $15 billion in 2025, is projected to expand significantly over the next decade, fueled by a Compound Annual Growth Rate (CAGR) of 15%. This growth is propelled by several key factors: the proliferation of digital channels, the rise of personalized marketing strategies, the increasing adoption of cloud-based analytics solutions, and the growing demand for real-time data insights. Key market segments, including e-commerce and website analysis platforms, are witnessing particularly strong growth, as businesses leverage these platforms to improve conversion rates, customer retention, and overall business performance. The competitive landscape is marked by a mix of established players like Google and Adobe, alongside specialized analytics vendors such as Mixpanel and Amplitude. These companies are continuously innovating, incorporating advanced technologies like AI and machine learning to enhance their offerings and cater to evolving business needs. The geographic distribution of the market is diverse, with North America and Europe currently holding the largest market shares. However, rapid growth is anticipated in Asia-Pacific regions like India and China, fueled by increasing internet penetration and digital adoption. While the market faces certain restraints, such as data privacy concerns and the complexity of implementing big data analytics solutions, these challenges are being mitigated by advancements in data security technologies and user-friendly analytics platforms. The ongoing trend towards real-time analytics and predictive modeling will further drive market expansion, empowering businesses to make data-driven decisions with greater speed and accuracy. The forecast period of 2025-2033 promises substantial growth opportunities for both established players and emerging startups in this dynamic sector.

The Data Processing and Hosting Services industry has transformed over the past decade, with the growth of cloud computing creating new markets. Demand surged in line with heightened demand from banks and a rising number of mobile connections across Europe. Many companies regard cloud computing as an innovative way of reducing their operating costs, which has led to the introduction of new services that make the sharing of data more efficient. Over the five years through 2025, revenue is expected to hike at a compound annual rate of 4.3% to €113.5 billion, including a 5.6% jump in 2025. Industry profit has been constrained by pricing pressures between companies and regions. Investments in new-generation data centres, especially in digital hubs like Frankfurt, London, and Paris, have consistently outpaced available supply, underlining the continent’s insatiable appetite for processing power. Meanwhile, 5G network roll-outs and heightened consumer expectations for real-time digital services have made agile hosting and robust cloud infrastructure imperative, pushing providers to invest in both core and edge data solutions. Robust growth has been fuelled by rapid digitalisation, widespread cloud adoption, and exploding demand from sectors such as e-commerce and streaming. Scaling cloud infrastructure, driven by both established giants, like Amazon Web Services (AWS), Microsoft Azure and Google Cloud and nimble local entrants, has allowed the industry to keep pace with unpredictable spikes in online activity and increasingly complex data needs. Rising investment in data centre capacity and the proliferation of high-availability hosting have significantly boosted operational efficiency and market competitiveness, with revenue growth closely tracking the boom in cloud and streaming services across the continent. Industry revenue is set to grow moving forward as European businesses incorporate data technology into their operations. Revenue is projected to boom, growing at a compound annual rate of 10.3% over the five years through 2030, to reach €185.4 billion. Growth is likely to be assisted by ongoing cloud adoption, accelerated 5G expansion, and soaring investor interest in hyperscale and sovereign data centres. Technical diversification seen in hybrid cloud solutions, edge computing deployments, and sovereign clouds, will create significant opportunities for incumbents and disruptors alike. Pricing pressures, intensified by global hyperscalers’ economies of scale and assertive licensing strategies, will pressurise profit, especially for smaller participants confronting rising capital expenditure and compliance costs.

The Web 2.0 Data Center market is experiencing robust growth, driven by the increasing demand for cloud computing, big data analytics, and the proliferation of internet-connected devices. The market, estimated at $500 billion in 2025, is projected to expand significantly over the next decade, fueled by continuous technological advancements and evolving business needs. Key drivers include the rising adoption of virtualization and containerization technologies, enhancing efficiency and scalability. Furthermore, the increasing focus on edge computing, enabling faster data processing closer to the source, is a major growth catalyst. The expanding use of artificial intelligence (AI) and machine learning (ML) for various applications also significantly contributes to market expansion. Major players such as Dell, IBM, AWS, and others are investing heavily in research and development to enhance their offerings, leading to increased competition and innovation within the sector. However, challenges remain, including concerns around data security and privacy, the complexities of managing large-scale data centers, and the need for skilled professionals. Despite these challenges, the long-term outlook for the Web 2.0 Data Center market is positive. The ongoing digital transformation across various industries and the increasing reliance on digital infrastructure suggest sustained market growth. Segmentation within the market is evident, with diverse offerings catering to specific needs and applications. The geographic distribution of the market is expected to be largely influenced by regions with established digital ecosystems and substantial investment in technological infrastructure. As companies strive to optimize their data storage and processing capabilities, the demand for robust and scalable Web 2.0 Data Centers is set to remain high, presenting significant opportunities for growth in the coming years. The competitive landscape, while intense, fosters innovation and helps ensure the market remains dynamic and responsive to evolving customer requirements.

Conceptual overview of the MataNui Grid data infrastructure as well as details on the performance evaluation conducted using the Griffin GridFTP server and RESTful Web Service against a MongoDB/GridFS-based MataNui storage.

This content is augmenting the content of to the paper "MataNui - A Distributed Storage Infrastructure for Scientific Data" in the proceedings of the International Conference on Computational Science (ICCS) 2013, published in Elsevier's Procedia Computer Science series [http://www.elsevier.com/wps/find/journaldescription.cws_home/719435/description].

The Big Data Analytics and Hadoop market is experiencing robust growth, driven by the exponential increase in data volume across industries and the rising need for advanced analytics to extract actionable insights. The market's expansion is fueled by several key factors, including the increasing adoption of cloud-based big data solutions, the growing demand for real-time analytics, and the emergence of sophisticated analytical techniques like machine learning and AI. Businesses across various sectors, from healthcare and finance to retail and manufacturing, are leveraging big data analytics to improve operational efficiency, enhance customer experience, and gain a competitive edge. The market is segmented by deployment model (cloud, on-premise), organization size (small, medium, large enterprises), and industry vertical, each exhibiting unique growth trajectories. While the initial investment in infrastructure and skilled personnel can pose a challenge for some organizations, the long-term benefits of improved decision-making and enhanced business outcomes far outweigh these initial hurdles. The competitive landscape is marked by both established players and emerging startups, leading to innovation and continuous improvement in the technology and services offered. The forecast period of 2025-2033 anticipates sustained growth, with a projected Compound Annual Growth Rate (CAGR) significantly influenced by technological advancements, government initiatives promoting data-driven decision making, and the increasing adoption of big data solutions by small and medium-sized enterprises. Companies like Cloudera, Hortonworks, and Amazon Web Services are key players, shaping the market with their innovative solutions and expanding market reach. However, factors like data security concerns and the lack of skilled professionals remain challenges that require ongoing attention. The market's success hinges on addressing these challenges through robust security measures, investment in talent development, and continued innovation in areas such as data governance and data visualization. Future growth will be significantly influenced by the successful integration of big data analytics into business strategies and the continued development of accessible and user-friendly platforms.

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The Big Data Analysis Software market is experiencing robust growth, driven by the increasing volume of data generated across various sectors and the rising need for actionable insights. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors. The widespread adoption of cloud-based solutions offers scalability, cost-effectiveness, and accessibility, accelerating market penetration. Furthermore, the growing demand for real-time analytics across industries like banking, manufacturing, and government is a major driver. Specific trends include the increasing integration of AI and machine learning into analytics platforms, enhancing predictive capabilities and automating processes. However, challenges remain, such as data security concerns, the complexity of implementing and managing big data solutions, and the skills gap in data science expertise. These factors represent potential restraints on market growth, though ongoing technological advancements and increased investment in data literacy initiatives are mitigating these issues. The market is segmented by deployment type (cloud-based and on-premises) and application (banking, manufacturing, consultancy, government, and others), with cloud-based solutions dominating due to their inherent advantages. The competitive landscape is highly dynamic, featuring both established technology giants like Google, Amazon, and IBM, alongside specialized software providers such as Rohde & Schwarz and Qlucore. The diversity of players indicates a wide range of solutions catering to diverse needs and market segments. Regional growth is expected to be diverse, with North America and Europe maintaining substantial market shares due to early adoption and advanced technological infrastructure. However, rapidly developing economies in Asia-Pacific and the Middle East & Africa are poised for significant growth, presenting lucrative opportunities for market expansion. The forecast period (2025-2033) anticipates continued market expansion, driven by technological innovations, increasing data volumes, and growing adoption across various industries and geographies. The market's long-term prospects remain positive, indicating a significant return on investment for businesses involved in its development and implementation.

Apache Hadoop is the central software project, beside Apache SOLR, and Apache Lucene (SW, software). Companies which offer Hadoop distributions and Hadoop based solutions are the central companies in the scope of the study (HV, hardware vendors). Other companies started very early with Hadoop related projects as early adopters (EA). Global players (GP) are affected by this emerging market, its opportunities and the new competitors (NC). Some new but highly relevant companies like Talend or LucidWorks have been selected because of their obvious commitment to the open source ideas. Widely adopted technologies with a relation to the selected research topic are represented by the group TEC.

The Hadoop Big Data Analytics market, valued at $4053.9 million in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 12.4% from 2025 to 2033. This growth is fueled by the increasing volume and velocity of data generated across diverse industries, coupled with a rising demand for advanced analytics capabilities to extract actionable insights. Key drivers include the need for improved operational efficiency, enhanced decision-making, and competitive advantage. The market is segmented by application (Large Enterprise and SME) and by type (Data Ingestion Tools, Data Processing Tools, Data Query and Analysis Tools, and Other). Large enterprises currently dominate the application segment, driven by their significant data volumes and sophisticated analytics needs. However, increasing adoption of cloud-based solutions and affordable data analytics tools is fueling growth in the SME segment. Data Ingestion Tools represent a significant portion of the market, reflecting the crucial initial step in the data analytics lifecycle. The leading companies in this space – Cloudera, MapR Technologies, IBM, Amazon Web Services, Microsoft, Google, VMware, Oracle, Teradata, and SAS – are constantly innovating, expanding their product portfolios, and engaging in strategic partnerships to maintain a competitive edge. Geographic expansion, particularly in rapidly developing economies of Asia Pacific and Middle East & Africa, further contributes to market expansion. The forecast period (2025-2033) anticipates continuous market evolution. Trends such as the increasing adoption of cloud-based Hadoop solutions, the growing popularity of real-time analytics, and the rise of artificial intelligence (AI) and machine learning (ML) integrated with Hadoop are expected to shape the market landscape. However, challenges remain, including the complexity of Hadoop implementation and the need for specialized skills to manage and analyze large datasets. Furthermore, data security concerns and regulatory compliance requirements pose restraints on market growth, although advancements in security technologies are mitigating these issues. The ongoing evolution of Hadoop towards more user-friendly interfaces and managed services is expected to drive wider adoption across various industries and business sizes in the years to come.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.