Stations and a table of download links for time-series data, from DWR's continuous environmental monitoring database. For more information, see DWR's Water Data Library, continuous data section: https://wdl.water.ca.gov/ContinuousData.aspx, where this data is also available.

Many capture-recapture surveys of wildlife populations operate in continuous time but detections are typically aggregated into occasions for analysis, even when exact detection times are available. This discards information and introduces subjectivity, in the form of decisions about occasion definition. We develop a spatio-temporal Poisson process model for spatially explicit capture-recapture (SECR) surveys that operate continuously and record exact detection times. We show that, except in some special cases (including the case in which detection probability does not change within occasion), temporally aggregated data do not provide sufficient statistics for density and related parameters, and that when detection probability is constant over time our continuous-time (CT) model is equivalent to an existing model based on detection frequencies. We use the model to estimate jaguar density from a camera-trap survey and conduct a simulation study to investigate the properties of a CT estimator and discrete-occasion estimators with various levels of temporal aggregation. This includes investigation of the effect on the estimators of spatio-temporal correlation induced by animal movement. The CT estimator is found to be unbiased and more precise than discrete-occasion estimators based on binary capture data (rather than detection frequencies) when there is no spatio-temporal correlation. It is also found to be only slightly biased when there is correlation induced by animal movement, and to be more robust to inadequate detector spacing, while discrete-occasion estimators with binary data can be sensitive to occasion length, particularly in the presence of inadequate detector spacing. Our model includes as a special case a discrete-occasion estimator based on detection frequencies, and at the same time lays a foundation for the development of more sophisticated CT models and estimators. It allows modelling within-occasion changes in detectability, readily accommodates variation in detector effort, removes subjectivity associated with user-defined occasions, and fully utilises CT data. We identify a need for developing CT methods that incorporate spatio-temporal dependence in detections and see potential for CT models being combined with telemetry-based animal movement models to provide a richer inference framework.

Mutual information (MI) is a powerful method for detecting relationships between data sets. There are accurate methods for estimating MI that avoid problems with “binning” when both data sets are discrete or when both data sets are continuous. We present an accurate, non-binning MI estimator for the case of one discrete data set and one continuous data set. This case applies when measuring, for example, the relationship between base sequence and gene expression level, or the effect of a cancer drug on patient survival time. We also show how our method can be adapted to calculate the Jensen–Shannon divergence of two or more data sets.

This is an early version of the continuous endpoint. It is feature-complete and provides access to the full continuous data record, and is being made available as we continue to work on performance improvements. Continuous data are collected via automated sensors installed at a monitoring location. They are collected at a high frequency and often at a fixed 15-minute interval. Depending on the specific monitoring location, the data may be transmitted automatically via telemetry and be available on WDFN within minutes of collection, while other times the delivery of data may be delayed if the monitoring location does not have the capacity to automatically transmit data. Continuous data are described by parameter name and parameter code (pcode). These data might also be referred to as "instantaneous values" or "IV".

Abstract

Access to up-to-date socio-economic data is a widespread challenge in Papua New Guinea and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 as a way to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See https://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details.

For PNG, after five rounds of data collection from 2020-2022, in April 2023 a monthly HFPS data collection commenced and continued for 18 months (ending September 2024) –on topics including employment, income, food security, health, food prices, assets and well-being. This followed an initial pilot of the data collection from January 2023-March 2023. Data for April 2023-September 2023 were a repeated cross section, while October 2023 established the first month of a panel, which is ongoing as of March 2025. For each month, approximately 550-1000 households were interviewed. The sample is representative of urban and rural areas but is not representative at the province level. This dataset contains combined monthly survey data for all months of the continuous HFPS in PNG. There is one date file for household level data with a unique household ID, and separate files for individual level data within each household data, and household food price data, that can be matched to the household file using the household ID. A unique individual ID within the household data which can be used to track individuals over time within households.

Geographic coverage

Urban and rural areas of Papua New Guinea

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The initial sample was drawn through Random Digit Dialing (RDD) with geographic stratification from a large random sample of Digicel’s subscribers. As an objective of the survey was to measure changes in household economic wellbeing over time, the HFPS sought to contact a consistent number of households across each province month to month. This was initially a repeated cross section from April 2023-Dec 2023. The resulting overall sample has a probability-based weighted design, with a proportionate stratification to achieve a proper geographical representation. More information on sampling for the cross-sectional monthly sample can be found in previous documentation for the PNG HFPS data.

A monthly panel was established in October 2023, that is ongoing as of March 2025. In each subsequent round of data collection after October 2024, the survey firm would first attempt to contact all households from the previous month, and then attempt to contact households from earlier months that had dropped out. After previous numbers were exhausted, RDD with geographic stratification was used for replacement households.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

he questionnaire, which can be found in the External Resources of this documentation, is in English with a Pidgin translation.

The survey instrument for Q1 2025 consists of the following modules: -1. Basic Household information, -2. Household Roster, -3. Labor, -4a Food security, -4b Food prices -5. Household income, -6. Agriculture, -8. Access to services, -9. Assets -10. Wellbeing and shocks -10a. WASH

Cleaning operations

The raw data were cleaned by the World Bank team using STATA. This included formatting and correcting errors identified through the survey’s monitoring and quality control process. The data are presented in two datasets: a household dataset and an individual dataset. The individual dataset contains information on individual demographics and labor market outcomes of all household members aged 15 and above, and the household data set contains information about household demographics, education, food security, food prices, household income, agriculture activities, social protection, access to services, and durable asset ownership. The household identifier (hhid) is available in both the household dataset and the individual dataset. The individual identifier (id_member) can be found in the individual dataset.

Continuous Data Protection Market Outlook

As per our latest research, the global Continuous Data Protection (CDP) market size reached USD 4.8 billion in 2024, driven by the increasing need for robust data security and real-time backup solutions across various industries. The market is exhibiting a strong compound annual growth rate (CAGR) of 12.1% from 2025 to 2033. By the end of 2033, the Continuous Data Protection market is forecasted to attain a value of approximately USD 13.5 billion. The primary growth factor is the rising frequency of ransomware attacks and data breaches, compelling organizations to invest in advanced data protection and disaster recovery solutions.

One of the major growth drivers for the Continuous Data Protection market is the exponential increase in data generation and digital transformation initiatives worldwide. Enterprises are generating massive volumes of data from a variety of sources, including IoT devices, cloud applications, and mobile endpoints. This surge in data, coupled with the critical need to ensure business continuity, has heightened the demand for CDP solutions. Unlike traditional backup systems, CDP offers real-time or near-real-time backup, minimizing data loss and enabling rapid recovery in the event of system failures or cyber incidents. As organizations become more data-centric, the adoption of continuous data protection technologies is expected to accelerate, particularly among sectors that handle sensitive or mission-critical information.

Another significant factor fueling the growth of the Continuous Data Protection market is the evolving regulatory landscape. Governments and regulatory bodies across the globe are implementing stringent data protection and privacy regulations, such as GDPR in Europe and CCPA in California. These regulations require organizations to maintain robust data protection strategies, including real-time backup and rapid recovery capabilities. As non-compliance can lead to severe financial penalties and reputational damage, enterprises are increasingly turning to CDP solutions to ensure adherence to these mandates. The ability of CDP to provide point-in-time recovery and granular restoration of data aligns perfectly with regulatory requirements, further boosting market adoption.

Technological advancements and integration with cloud platforms are also shaping the trajectory of the Continuous Data Protection market. Modern CDP solutions are leveraging artificial intelligence, machine learning, and automation to enhance data backup, anomaly detection, and threat response. The proliferation of hybrid and multi-cloud environments has necessitated the development of CDP solutions that can seamlessly protect data across on-premises and cloud infrastructures. This trend is particularly prominent among large enterprises and organizations with distributed IT environments. Furthermore, the growing awareness of the financial and operational impacts of data loss is prompting even small and medium-sized enterprises to invest in continuous data protection, thus expanding the market’s addressable base.

From a regional perspective, North America continues to dominate the Continuous Data Protection market due to its advanced IT infrastructure, high adoption of cloud computing, and heightened focus on cybersecurity. However, the Asia Pacific region is witnessing the fastest growth, attributed to rapid digitalization, increasing investments in IT security, and rising awareness about data protection among enterprises. Europe also holds a significant market share, driven by strict data privacy regulations and a mature enterprise landscape. The Middle East & Africa and Latin America are emerging markets, where growing digital transformation and regulatory developments are expected to create new opportunities for CDP vendors in the coming years.

Component Analysis

The Continuous Data Protection market is segmented by component into software, hardware, and services. The software segment holds the largest share, accounting for more than 55% of the global m

This lesson helps students know some of the options for how to graph grouped continuous data (such as those involved in doing a t-test or ANOVA) and how to choose the best option.

WMD, Weighted Mean Difference; CI, confidence interval.*The numerals indicate the total number of cases and controls.†Pheterogeneity less than 0.1 was considered significant.Clinical Endpoints: Continuous Data.

The size of the Continuous Data Protection and Recovery Software market was valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2032, with an expected CAGR of XX% during the forecast period.

Abstract

Access to up-to-date socio-economic data is a widespread challenge in Tonga and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 as a way to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See https://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details. For Tonga, after two rounds of data collection from in 2022, monthly HFPS data collection commenced in April 2023 and continued until November 2024 (but with some gaps in the months of collection). The survey collected socio-economic data on topics including employment, income, food security, health, food prices, assets and well-being. Each month of collection has approximately 415 households in the sample and is representative of urban and rural areas. This dataset contains combined monthly survey data for all months of the continuous HFPS in Tonga.

Geographic coverage

National urban and rural areas (5 islands): Tongatapu, Vava'u, Ha'apai, Eua, Ongo Niua

Analysis unit

Individual and household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tonga High Frequency Phone Survey (HFPS) monthly sample was generated in three ways. The first method is Random Digit Dialing (RDD) process covering all cell telephone numbers active at the time of the sample selection. The RDD methodology generates virtually all possible telephone numbers in the country under the national telephone numbering plan and then draws a random sample of numbers. This method guarantees full coverage of the population with a phone.

First, a large first-phase sample of cell phone numbers was selected and screened through an automated process to identify the active numbers. Then, a smaller second-phase sample was selected from the active residential numbers identified in the first-phase sample and was delivered to the data collection team to be called by the interviewers. When a cell phone was called, the call answerer was interviewed as long as he or she was 18 years of age or above and knowledgeable about the household activities.

It was initially planned to stratify the sample by island group based on the phone number prefixes. However, this was not feasible given the high internal migration across islands and the atypical assignment of phone number prefixes across islands in Tonga. The raw sample is overrepresenting urban areas and the population of Tongatapu.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire was developed in both English and Tongan and can be found in this documentation in Excel format. Sections of the Questionnaire are provided below: 1. Interview information and Basic information 2. Household roster 3. Labor 4. Food security and food prices 5. Household income 6. Agriculture 7. Social protection 8. Access to services 9. Assets 10. Education 11. Follow up

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the survey firm and the World Bank team. Data cleaning mainly included formatting, relabeling, and excluding survey monitoring variables (e.g., interview start and end times). Data was edited using the software Stata.

The global Continuous Data Protection and Recovery Software market is poised for robust growth, projected to reach an estimated market size of $25,000 million by 2025, with a projected Compound Annual Growth Rate (CAGR) of 15% through 2033. This expansion is primarily fueled by the escalating volume of digital data generated across industries and the paramount importance of business continuity in the face of cyber threats and system failures. Organizations are increasingly recognizing CDP and recovery solutions not as mere IT utilities but as critical components of their overall risk management strategies, safeguarding against potential financial losses, reputational damage, and regulatory non-compliance. The demand for instant data recovery and minimal downtime is driving innovation and adoption, particularly within sectors such as banking, securities, and enterprise resource planning (ERP) systems, where data integrity and availability are non-negotiable. Key drivers propelling this market forward include the rising sophistication of cyberattacks, the growing adoption of cloud computing and hybrid environments, and the increasing regulatory pressure for data resilience. CDP and recovery software plays a vital role in enabling organizations to meet these challenges by providing granular recovery options and near real-time data protection. The market is segmented across various applications, including Bank, Securities Company, Enterprise ERP System, Campus Card System, and Hospital HIS System, each with unique data protection needs. While cloud deployments are gaining significant traction due to their scalability and cost-effectiveness, on-premise solutions continue to cater to organizations with specific security or regulatory requirements. Leading players such as DELL EMC, Commvault, IBM, Veritas, and Veeam are actively investing in research and development to offer advanced features and cater to evolving customer demands, further shaping the competitive landscape and driving market expansion. This comprehensive report delves into the dynamic market for Continuous Data Protection and Recovery (CDP) software, offering a detailed analysis of its current landscape, historical trajectory, and future projections. With a study period spanning from 2019 to 2033, and a base year of 2025, this research provides invaluable insights into market concentration, evolving trends, dominant regions and segments, product innovations, and the strategic moves of key industry players. The estimated market size is projected to reach $25 million by the end of the forecast period in 2033, indicating substantial growth.

The Alabama Real-time Coastal Observing System (ARCOS) with support of the Dauphin Island Sea Lab is a network of continuously sampling observing stations that collect observations of meteorological and hydrographic data from fixed stations operating across coastal Alabama. Data were collected from 2003 through the present and include parameters such as air temperature, relative humidity, solar and quantum radiation, barometric pressure, wind speed, wind direction, precipitation amounts, water temperature, salinity, dissolved oxygen, water height, and other water quality data. Stations, when possible, are designed to collect the same data in the same way, though there are exceptions given unique location needs (see individual accession abstracts for details). Stations are strategically placed to sample across salinity gradients, from delta to offshore, and the width of the coast.

This table contains continuous temperature data for historic and inactive groundwater bores (non-SOBN), previously available on the Water Measurement Information System (WMIS).

Abstract

Access to up-to-date socio-economic data is a widespread challenge in Vanuatu and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See https://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details.

For Vanuatu, data for December 2023 – January 2025 was collected with each month having approximately 1000 households in the sample and is representative of urban and rural areas but is not representative at the province level. This dataset contains combined monthly survey data for all months of the continuous HFPS in Vanuatu. There is one date file for household level data with a unique household ID. And a separate file for individual level data within each household data, that can be matched to the household file using the household ID, and which also has a unique individual ID within the household data which can be used to track individuals over time within households, where the data is panel data.

Geographic coverage

National, urban and rural. Six provinces were covered by this survey: Sanma, Shefa, Torba, Penama, Malampa and Tafea.

Analysis unit

Household and individuals.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Vanuatu High Frequency Phone Survey (HFPS) sample is drawn from the list of customer phone numbers (MSIDNS) provided by Digicel Vanuatu, one of the country’s two main mobile providers. Digicel’s customer base spans all regions of Vanuatu. For the initial data collection, Digicel filtered their MSIDNS database to ensure a representative distribution across regions. Recognizing the challenge of reaching low-income respondents, Digicel also included low-income areas and customers with a low-income profile (defined by monthly spending between 50 and 150 VT), as well as those with only incoming calls or using the IOU service without repayment. These filtered lists were then randomized, and enumerators began calling the numbers.

This approach was used to complete the first round of 1,000 interviews. The respondents from this first round formed a panel to be surveyed monthly. Each month, phone numbers from the panel are contacted until all have been interviewed, at which point new phone numbers (fresh MSIDNS from Digicel’s database) are used to replace those that have been exhausted. These new respondents are then added to the panel for future surveys.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire was developed in both English and Bislama. Sections of the Questionnaire:

-Interview Information -Household Roster (separate modules for new households and returning households) -Labor (separate modules for new households and returning households) -Food Security
-Household Income -Agriculture
-Social Protection
-Access to Services -Assets -Perceptions -Follow-up

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the survey firm and the World Bank team. Data cleaning mainly included formatting, relabeling, and excluding survey monitoring variables (e.g., interview start and end times). Data was edited using the software STATA.

The data are presented in two datasets: a household dataset and an individual dataset. The total number of observations is 13,779 in the household dataset and 77,501 in the individual dataset. The individual dataset contains information on individual demographics and labor market outcomes of all household members aged 15 and above, and the household data set contains information about household demographics, education, food security, household income, agriculture activities, social protection, access to services, and durable asset ownership. The household identifier (hhid) is available in both the household dataset and the individual dataset. The individual identifier (hhid_mem) can be found in the individual dataset.

Response rate

In November 2024, a total of 7,874 calls were made. Of these, 2,251 calls were successfully connected, and 1,000 respondents completed the survey. By February 2024, the sample was fully comprised of returning respondents, with a re-contact rate of 99.9 percent.

The ALTUS Cloud Electrification Study (ACES) was Based at the Naval Air Facility Key West in Florida. ACES researchers in August 2002 conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, it allowed scientists to collect cloud electrification data for the first time from above the storm from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely, and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil magnetometer, Accelerometers, Gerdien Conductivity Prove, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels.

The global Continuous Data Protection (CDP) software market is poised for robust expansion, projected to reach a substantial market size of approximately $6,800 million by 2025, with an anticipated Compound Annual Growth Rate (CAGR) of around 12.5% through 2033. This significant growth is fueled by the escalating need for near-zero downtime and rapid data recovery across various industries, driven by an increasing volume of critical business data and the ever-present threat of cyberattacks and operational failures. The financial industry and healthcare sectors are leading the adoption of CDP solutions due to stringent regulatory compliance requirements and the mission-critical nature of their data, where even a few minutes of downtime can result in substantial financial losses and reputational damage. The burgeoning e-commerce landscape also contributes significantly, demanding constant availability to serve a global customer base. The adoption of cloud-based CDP solutions is a dominant trend, offering scalability, cost-effectiveness, and enhanced flexibility compared to traditional on-premises deployments. This shift is further propelled by the increasing reliance on cloud infrastructure and the growing sophistication of cloud-native applications. However, the market also faces certain restraints, including the initial implementation costs and the complexity of integrating CDP solutions with existing IT infrastructures, particularly for legacy systems. Geographically, North America is expected to maintain its leading position, driven by early adoption of advanced technologies and a strong presence of major CDP vendors. Asia Pacific, with its rapidly digitizing economies and increasing awareness of data protection, is anticipated to exhibit the highest growth rate in the forecast period. Key players like Veeam, Acronis, Zerto, and Dell EMC are actively innovating, offering advanced features such as granular recovery, ransomware protection, and seamless integration with hybrid cloud environments, thereby shaping the competitive landscape and driving market evolution. This in-depth report provides a comprehensive analysis of the Continuous Data Protection (CDP) software market, forecasting its trajectory from 2019 to 2033. With a base year of 2025 and an estimated market size exceeding $15,000 million in the same year, the market is poised for significant expansion throughout the forecast period (2025-2033). The historical period (2019-2024) has laid the groundwork for understanding the foundational growth drivers and adoption patterns of CDP solutions across diverse industries. This report delves into the intricacies of market concentration, key trends, regional dominance, product insights, driving forces, challenges, emerging trends, growth catalysts, leading players, and significant developments shaping the CDP landscape.

Continuous Data Protection Platform Market Outlook

According to our latest research, the Global Continuous Data Protection Platform market size was valued at $2.1 billion in 2024 and is projected to reach $7.3 billion by 2033, expanding at a CAGR of 14.7% during 2024–2033. One of the major factors driving the growth of the Continuous Data Protection Platform market is the mounting need for robust data security and real-time backup solutions across industries. With the exponential growth of digital data, organizations are increasingly prioritizing business continuity, compliance, and cyber-resilience, all of which are fueling investments in continuous data protection platforms that offer seamless backup, instant recovery, and advanced data integrity features.

Regional Outlook

North America currently holds the largest share of the Continuous Data Protection Platform market, accounting for over 38% of global revenue in 2024. The region's dominance is primarily attributed to its mature IT infrastructure, high adoption of advanced cybersecurity protocols, and a strong regulatory framework mandating stringent data protection. Major economies such as the United States and Canada have witnessed rapid deployment of continuous data protection solutions, particularly in sectors like BFSI, healthcare, and government, where data integrity and uptime are mission-critical. The presence of leading technology vendors, coupled with a robust ecosystem of managed service providers, has further accelerated market penetration. Additionally, North American enterprises are early adopters of cloud-based data protection solutions, leveraging hybrid and multi-cloud environments to ensure seamless business operations and regulatory compliance.

The Asia Pacific region is projected to be the fastest-growing market for Continuous Data Protection Platforms, with a remarkable CAGR of 18.2% from 2024 to 2033. This rapid growth is driven by increasing digital transformation initiatives, surging investments in IT infrastructure, and a rising incidence of cyberattacks and ransomware threats. Countries such as China, India, Japan, and South Korea are witnessing a surge in demand for advanced data protection solutions as businesses expand their digital footprints and adopt cloud technologies. The proliferation of small and medium enterprises (SMEs) in the region, coupled with government-led digitalization programs, is further propelling market growth. Strategic collaborations between global technology providers and regional players are also fostering innovation and accelerating the adoption of continuous data protection platforms in Asia Pacific.

In emerging economies across Latin America, the Middle East, and Africa, the Continuous Data Protection Platform market is experiencing gradual adoption, albeit at a slower pace compared to developed regions. Factors such as limited IT budgets, lack of skilled cybersecurity professionals, and fragmented regulatory frameworks pose significant challenges to widespread implementation. However, as digitalization accelerates and awareness around data security grows, organizations in these regions are increasingly exploring continuous data protection solutions to safeguard critical business information and ensure compliance with evolving data privacy laws. Localized demand is also being shaped by sector-specific requirements, such as in government, banking, and healthcare, where data loss can have severe operational and reputational repercussions. Tailored solutions and capacity-building initiatives are expected to gradually bridge the adoption gap in these markets.

Report Scope

Continuous Data Protection Platform Market Outlook

As per our latest research, the global Continuous Data Protection Platform market size reached USD 5.8 billion in 2024, with a robust compound annual growth rate (CAGR) of 11.7%. This dynamic market is primarily driven by the increasing need for real-time data backup and recovery solutions across industries. By 2033, the market is forecasted to reach USD 15.9 billion, highlighting significant expansion opportunities. The surge in cyber threats, stringent regulatory requirements, and the exponential growth in enterprise data volumes are among the key factors fueling this upward trajectory.

One of the most significant growth factors for the Continuous Data Protection Platform market is the escalating frequency and sophistication of cyberattacks and ransomware incidents globally. Organizations are increasingly recognizing the limitations of traditional backup solutions, which often leave critical gaps between scheduled backups, resulting in potential data loss. Continuous Data Protection (CDP) platforms address these vulnerabilities by capturing and saving every change made to data in real time, thereby ensuring near-zero data loss and enabling rapid recovery. As businesses become more data-centric and digital transformation accelerates, the demand for robust data protection mechanisms such as CDP is expected to rise substantially, especially in sectors like banking, healthcare, and retail where data integrity and availability are paramount.

Another pivotal driver is the growing adoption of cloud computing and hybrid IT environments. Enterprises are migrating their workloads to cloud platforms for scalability, cost efficiency, and flexibility, but this shift also introduces new data protection challenges. CDP solutions are evolving to seamlessly integrate with public, private, and hybrid cloud infrastructures, providing unified data protection across diverse environments. The ability to protect data regardless of where it resides—on-premises, in the cloud, or within edge devices—makes CDP platforms indispensable for modern organizations. Moreover, regulatory frameworks such as GDPR, HIPAA, and CCPA are compelling organizations to invest in advanced data protection solutions that ensure compliance and minimize the risk of penalties associated with data breaches.

The proliferation of data generated by emerging technologies such as IoT, artificial intelligence, and big data analytics is further propelling the demand for Continuous Data Protection Platforms. Enterprises are dealing with unprecedented data volumes and velocities, which necessitate always-on backup and instant recovery capabilities. CDP platforms not only provide continuous data capture but also facilitate granular recovery options, enabling businesses to restore data to any point in time. This is particularly valuable in environments with mission-critical applications, where even minimal downtime or data loss can have severe operational and financial repercussions. As a result, the integration of CDP solutions is becoming a strategic priority for organizations aiming to enhance their data resilience and business continuity frameworks.

From a regional perspective, North America currently dominates the Continuous Data Protection Platform market, accounting for the largest revenue share in 2024. The region’s leadership is attributed to the presence of major technology vendors, early adoption of advanced IT security solutions, and a highly regulated business environment. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid digitalization, increasing cloud adoption, and rising awareness about data protection among enterprises and government bodies. Europe also holds a significant market share, supported by stringent data protection regulations and a mature IT infrastructure. The Middle East & Africa and Latin America are witnessing steady growth as organizations in these regions invest in modernizing their data protection strategies to support digital transformation initiatives.

The goal of this study was to develop a suite of inter-related water quality monitoring approaches capable of modeling and estimating the spatial and temporal gradients of particulate and dissolved total mercury (THg) concentration, and particulate and dissolved methyl mercury (MeHg), concentration, in surface waters across the Sacramento / San Joaquin River Delta (SSJRD). This suite of monitoring approaches included: a) data collection at fixed continuous monitoring stations (CMS) outfitted with in-situ sensors, b) spatial mapping using boat-mounted flow-through sensors, and c) satellite-based remote sensing. The focus of this specific child page is to document the temporal high-resolution (15 minute) in-situ sensor data collected at the four primary CMS locations. The four primary CMS locations chosen for this study included: a) a Sacramento R. dominated site in the northern portion of the Delta (Freeport, FPT, USGS Station_no. 11447650); b) a site in western portion of the cen ...

Continuous Data Protection Market Outlook

According to our latest research, the global Continuous Data Protection (CDP) market size reached USD 3.2 billion in 2024, demonstrating robust momentum driven by the critical need for real-time data backup and restoration across various industries. The market is expected to expand at a compound annual growth rate (CAGR) of 12.8% from 2025 to 2033, reaching a projected value of USD 9.5 billion by 2033. This impressive growth is primarily fueled by the rising frequency of ransomware attacks, stringent regulatory requirements for data integrity, and the increasing adoption of digital transformation initiatives across both large enterprises and small and medium-sized businesses.

One of the most significant growth factors for the Continuous Data Protection market is the escalating prevalence of cyber threats and data breaches, which has compelled organizations to prioritize robust backup and disaster recovery solutions. As businesses increasingly rely on digital operations, the risk associated with data loss, corruption, and unauthorized access has intensified. Continuous Data Protection offers an advanced layer of security by ensuring that every change to critical data is captured and stored in real-time, minimizing the risk of data loss between scheduled backups. This capability is particularly vital for industries such as BFSI, healthcare, and government, where data sensitivity and compliance requirements are paramount. Furthermore, the proliferation of remote work and distributed IT environments has elevated the importance of seamless and uninterrupted data protection, further accelerating market demand.

Another pivotal driver is the surge in regulatory mandates and compliance standards, such as GDPR, HIPAA, and PCI DSS, which require organizations to maintain comprehensive records of data transactions and ensure rapid recoverability in the event of a breach or failure. Continuous Data Protection solutions enable organizations to meet these stringent requirements by offering granular restore points, automated versioning, and audit-ready reporting. The ability to recover data to any point in time not only reduces the operational impact of data loss incidents but also enhances organizational resilience and customer trust. As regulatory frameworks continue to evolve and expand globally, the demand for advanced CDP solutions is expected to witness sustained growth, particularly among highly regulated sectors.

Technological advancements and the maturation of cloud-based architectures have also played a crucial role in propelling the Continuous Data Protection market. The integration of artificial intelligence and machine learning into CDP platforms has enabled predictive analytics, intelligent anomaly detection, and automated remediation, significantly improving backup efficiency and reducing recovery times. Additionally, the growing adoption of hybrid and multi-cloud strategies has driven the need for flexible, scalable, and interoperable data protection solutions that can seamlessly operate across diverse environments. Vendors are increasingly focusing on delivering cloud-native CDP offerings that cater to the unique needs of modern enterprises, thereby expanding their addressable market and fostering innovation.

From a regional perspective, North America continues to dominate the global Continuous Data Protection market, accounting for the largest revenue share in 2024, followed closely by Europe and the Asia Pacific. The high concentration of technologically advanced enterprises, early adoption of digital transformation, and a strong regulatory landscape have positioned North America as a key growth engine for the industry. Meanwhile, the Asia Pacific region is anticipated to exhibit the fastest CAGR during the forecast period, driven by rapid digitalization, expanding IT infrastructure, and increasing awareness of data protection best practices among emerging economies. Europe remains a significant market, supported by strict data privacy regulations and a mature enterprise sector. Latin America and the Middle East & Africa are also witnessing steady adoption, albeit from a smaller base, as organizations in these regions recognize the strategic value of continuous data protection in safeguarding business continuity.

Component Analysis

The Continuous Data Protection market is segmented by component into software, hardware, and services, each playing a pivotal role in the overall v