According to a survey conducted in May 2024, almost 15 percent of cloud service operators in Japan do not make it clear through a contract or agreement how they handle customer data after the termination of a cloud service. While some of those companies go on to delete the data, others answered that they wait for inquiries or were asked to store the data after the termination of the service.

Corrections to SLR tracking data collected from various tables on CDDIS, resolutions from the ILRS/ASC (AWG) meetings, the T2L2 @ Jason-2 project (July 2008 to December 2017), the final results of the ILRS Station Systematic Error Monitoring--SSEM project, amended with results from its 2023 extension as an ongoing project, SSEM-X.

The Sassen BF1 soil moisture station is part of an agrometeorological test site and aims at supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration.The site is intensively used for practical tests of remote sensing data integration in agricultural land management practices. First measurement infrastructure was installed by DLR in 1999 and instrumentation was intensified in 2011 and later as the site became part of the TERENO-NE observatory. The soil moisture station station Sassen BF1 was installed in 2012. It is located next to a pylon on a crest of an undulating field. The station is equipped with sensor for measuring the following variables: ScemeSpadeSoilMoisture_Spade_2_Temperature, ScemeSpadeSoilMoisture_Spade_6_Temperature, ScemeSpadeSoilMoisture_Spade_1, ScemeSpadeSoilMoisture_Spade_2, ScemeSpadeSoilMoisture_Spade_3, ScemeSpadeSoilMoisture_Spade_4, ScemeSpadeSoilMoisture_Spade_5 and ScemeSpadeSoilMoisture_Spade_6. The current version of this dataset is 1.5. This version includes two additional years of data (from-year to-year)and a revised version of the data flags. New authors were added for this new version: Alice Künzel (GFZ Potsdam), Christian Budach (GFZ Potsdam), Nils Brinckmann (GFZ Potsdam), Max Wegener (DLR Neustrelitz) and Klemens Schmidt (DLR Neustrelitz).A detailed overview on all changes is provided in the station description file. Older versions are available in the 'previous_versions' subfolder via the Data Download link. A first version of this data was provided under http://doi.org/ containing the measured data only. The dataset is also available through the TERENO Data Discovery Portal. The datafile will be extended once per year as more data is acquired at the stations and the metadatafile will be updated. New columns for new variables will be added as necessary. In case of changes in data processing, which will result in changes of historical data, an new Version of this dataset will be published using a new doi. New data will be added after a delay of several months to allow manual interference with the quality control process. During October 2020 a Bug in the published data was detected and a new version of the datasets was released from beginning until mid 2020. Data processing was done using DMRP version: 1.8.4. Metadataprocessing was done using DMETA version: 1.2.0.

Ethical Data ManagementExecutive SummaryIn the age of data and information, it is imperative that the City of Virginia Beach strategically utilize its data assets. Through expanding data access, improving quality, maintaining pace with advanced technologies, and strengthening capabilities, IT will ensure that the city remains at the forefront of digital transformation and innovation. The Data and Information Management team works under the purpose:“To promote a data-driven culture at all levels of the decision making process by supporting and enabling business capabilities with relevant and accurate information that can be accessed securely anytime, anywhere, and from any platform.”To fulfill this mission, IT will implement and utilize new and advanced technologies, enhanced data management and infrastructure, and will expand internal capabilities and regional collaboration.Introduction and JustificationThe Information technology (IT) department’s resources are integral features of the social, political and economic welfare of the City of Virginia Beach residents. In regard to local administration, the IT department makes it possible for the Data and Information Management Team to provide the general public with high-quality services, generate and disseminate knowledge, and facilitate growth through improved productivity.For the Data and Information Management Team, it is important to maximize the quality and security of the City’s data; to develop and apply the coherent management of information resources and management policies that aim to keep the general public constantly informed, protect their rights as subjects, improve the productivity, efficiency, effectiveness and public return of its projects and to promote responsible innovation. Furthermore, as technology evolves, it is important for public institutions to manage their information systems in such a way as to identify and minimize the security and privacy risks associated with the new capacities of those systems.The responsible and ethical use of data strategy is part of the City’s Master Technology Plan 2.0 (MTP), which establishes the roadmap designed by improve data and information accessibility, quality, and capabilities throughout the entire City. The strategy is being put into practice in the shape of a plan that involves various programs. Although these programs was specifically conceived as a conceptual framework for achieving a cultural change in terms of the public perception of data, it basically covers all the aspects of the MTP that concern data, and in particular the open-data and data-commons strategies, data-driven projects, with the aim of providing better urban services and interoperability based on metadata schemes and open-data formats, permanent access and data use and reuse, with the minimum possible legal, economic and technological barriers within current legislation.Fundamental valuesThe City of Virginia Beach’s data is a strategic asset and a valuable resource that enables our local government carry out its mission and its programs effectively. Appropriate access to municipal data significantly improves the value of the information and the return on the investment involved in generating it. In accordance with the Master Technology Plan 2.0 and its emphasis on public innovation, the digital economy and empowering city residents, this data-management strategy is based on the following considerations.Within this context, this new management and use of data has to respect and comply with the essential values applicable to data. For the Data and Information Team, these values are:Shared municipal knowledge. Municipal data, in its broadest sense, has a significant social dimension and provides the general public with past, present and future knowledge concerning the government, the city, society, the economy and the environment.The strategic value of data. The team must manage data as a strategic value, with an innovative vision, in order to turn it into an intellectual asset for the organization.Geared towards results. Municipal data is also a means of ensuring the administration’s accountability and transparency, for managing services and investments and for maintaining and improving the performance of the economy, wealth and the general public’s well-being.Data as a common asset. City residents and the common good have to be the central focus of the City of Virginia Beach’s plans and technological platforms. Data is a source of wealth that empowers people who have access to it. Making it possible for city residents to control the data, minimizing the digital gap and preventing discriminatory or unethical practices is the essence of municipal technological sovereignty.Transparency and interoperability. Public institutions must be open, transparent and responsible towards the general public. Promoting openness and interoperability, subject to technical and legal requirements, increases the efficiency of operations, reduces costs, improves services, supports needs and increases public access to valuable municipal information. In this way, it also promotes public participation in government.Reuse and open-source licenses. Making municipal information accessible, usable by everyone by default, without having to ask for prior permission, and analyzable by anyone who wishes to do so can foster entrepreneurship, social and digital innovation, jobs and excellence in scientific research, as well as improving the lives of Virginia Beach residents and making a significant contribution to the city’s stability and prosperity.Quality and security. The city government must take firm steps to ensure and maximize the quality, objectivity, usefulness, integrity and security of municipal information before disclosing it, and maintain processes to effectuate requests for amendments to the publicly-available information.Responsible organization. Adding value to the data and turning it into an asset, with the aim of promoting accountability and citizens’ rights, requires new actions, new integrated procedures, so that the new platforms can grow in an organic, transparent and cross-departmental way. A comprehensive governance strategy makes it possible to promote this revision and avoid redundancies, increased costs, inefficiency and bad practices.Care throughout the data’s life cycle. Paying attention to the management of municipal registers, from when they are created to when they are destroyed or preserved, is an essential part of data management and of promoting public responsibility. Being careful with the data throughout its life cycle combined with activities that ensure continued access to digital materials for as long as necessary, help with the analytic exploitation of the data, but also with the responsible protection of historic municipal government registers and safeguarding the economic and legal rights of the municipal government and the city’s residents.Privacy “by design”. Protecting privacy is of maximum importance. The Data and Information Management Team has to consider and protect individual and collective privacy during the data life cycle, systematically and verifiably, as specified in the general regulation for data protection.Security. Municipal information is a strategic asset subject to risks, and it has to be managed in such a way as to minimize those risks. This includes privacy, data protection, algorithmic discrimination and cybersecurity risks that must be specifically established, promoting ethical and responsible data architecture, techniques for improving privacy and evaluating the social effects. Although security and privacy are two separate, independent fields, they are closely related, and it is essential for the units to take a coordinated approach in order to identify and manage cybersecurity and risks to privacy with applicable requirements and standards.Open Source. It is obligatory for the Data and Information Management Team to maintain its Open Data- Open Source platform. The platform allows citizens to access open data from multiple cities in a central location, regional universities and colleges to foster continuous education, and aids in the development of data analytics skills for citizens. Continuing to uphold the Open Source platform with allow the City to continually offer citizens the ability to provide valuable input on the structure and availability of its data. Strategic areasIn order to deploy the strategy for the responsible and ethical use of data, the following areas of action have been established, which we will detail below, together with the actions and emblematic projects associated with them.In general, the strategy pivots on the following general principals, which form the basis for the strategic areas described in this section.Data sovereigntyOpen data and transparencyThe exchange and reuse of dataPolitical decision-making informed by dataThe life cycle of data and continual or permanent accessData GovernanceData quality and accessibility are crucial for meaningful data analysis, and must be ensured through the implementation of data governance. IT will establish a Data Governance Board, a collaborative organizational capability made up of the city’s data and analytics champions, who will work together to develop policies and practices to treat and use data as a strategic asset.Data governance is the overall management of the availability, usability, integrity and security of data used in the city. Increased data quality will positively impact overall trust in data, resulting in increased use and adoption. The ownership, accessibility, security, and quality, of the data is defined and maintained by the Data Governance Board.To improve operational efficiency, an enterprise-wide data catalog will be created to inventory data and track metadata from various data sources to allow for rapid data asset discovery. Through the data catalog, the city will

The Data Management Platform Market report segments the industry into Functionality (First Party, Second Party, Third Party), Data Source (Web Analytics Tool, Mobile Web and Apps, CRM Data, POS Data, Social Networks), End-User (Ad Agencies, Marketers, Publishers), and Geography (North America, Europe, Asia, Australia and New Zealand, Middle East and Africa, Latin America).

The Global AI Data Management Market size was valued at around USD 23.8 billion in 2023 & is estimated to grow at a CAGR of around 24% during the forecast period 2024-30.

This statistic shows the primary environment for workloads for data processing, analytics, and business intelligence in global organizations today and in two years. As of 2018, on-premises "traditional" resources and infrastructure" is the most prevalent environment for data processing, analytics, and business intelligence, with 35 percent of respondents stating that organization made use of this workload environment. That figure is projected to shrink to just eight percent in 2020.

Global AI Data Management Market size & share estimated to surpass USD 185.35 billion by 2032, to grow at a CAGR of 24.2% during the forecast period.

The global Streaming Data Processing System Software market is experiencing robust growth, projected to reach $7,578.2 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 14.5% from 2025 to 2033. This significant expansion is fueled by the increasing volume and velocity of data generated across diverse sectors, demanding real-time insights and analytics. Key drivers include the rising adoption of cloud-based solutions offering scalability and cost-effectiveness, coupled with the expanding need for efficient data processing in applications like financial services (high-frequency trading, fraud detection), healthcare (real-time patient monitoring), and manufacturing (predictive maintenance). Furthermore, advancements in technologies such as AI and machine learning are enhancing the capabilities of these systems, leading to more sophisticated applications. While market restraints include the complexities associated with data integration and security concerns, the overall market trajectory remains exceptionally positive. The market segmentation reveals a strong preference for cloud-based solutions over on-premises deployments, reflecting the ongoing shift towards cloud computing. Among application segments, Financial Services and Healthcare and Life Sciences currently lead, driven by their critical need for immediate data analysis. However, other sectors like Manufacturing/Supply Chain, Communications, Media & Entertainment, and Public Sector are rapidly adopting streaming data processing, contributing to the overall market expansion. The competitive landscape is intensely dynamic, featuring major technology players like Google, Microsoft, AWS, and Oracle, alongside specialized providers like Confluent and TIBCO. The geographic distribution of the market shows North America and Europe holding a significant share currently; however, Asia-Pacific is poised for rapid growth, driven by increasing digitalization and infrastructure investments in emerging economies like India and China. The market's future growth will hinge on continued technological innovation, expanding adoption across diverse sectors, and the development of robust security frameworks to address data privacy and integrity concerns.

Recent developments include: November 2023: Arcion, a reputable provider of real-time data replication technologies, was acquired by Databricks. By incorporating Arcion's capabilities, Databricks hopes to offer native solutions that facilitate the seamless replication and intake of data from different databases and SaaS applications., September 2023: With an emphasis on artificial intelligence, Salesforce, Inc. extended its strategic alliance with Google LLC, an American multinational technology firm, to integrate Google Workspace, a popular productivity tool, with Salesforce, the industry's top AI CRM. With the introduction of bidirectional connectors brought about by the partnership, users can now combine context from Google Workspace and Salesforce, including Google Calendar, Docs, Meet, Gmail, and more, to improve generative AI experiences across multiple platforms.. Key drivers for this market are: The exponential growth in data generated across industries is driving the need for AI-driven data management solutions to handle, store, and analyze large datasets efficiently. Potential restraints include: Implementing AI data management systems requires significant investment in technology, infrastructure, and talent, which can be a barrier for smaller organizations. Notable trends are: AI is increasingly being used to automate data governance tasks, such as data classification, lineage tracking, and compliance monitoring, ensuring that organizations maintain data integrity and adhere to regulations.

The Data Masking Market can be segmented into various product categories, including:Type: Dynamic data masking, static data masking, and tokenization.Component: Software, services, and appliances.Business Function: Sales and marketing, human resources, legal, finance, and operations. Recent developments include: Sept 2020: Atlantech Online announced they had lit Anthem Row with fiber. The tenants on 700 K Street, NW, and 800 K Street, can now enjoy high-speed Internet bandwidth at affordable prices. Atlantech's Hosted PBX Service service can be utilized by tenants adding to the company's legacy., Oct 2020: Vonage has joined forces with Hacktoberfest to promote and honor contributions made to the Open Source community. As part of their collaboration, Vonage will provide access to their GitHub repositories, code snippets, and demos, supporting and encouraging developers in their Open Source endeavors. Key drivers for this market are: The growing use of cloud computing and big data analytics has expanded the need for secure data handling practices, . Potential restraints include: Slow Adoption Rate Of Machine Learning, Deep Learning And Neural Networks, Lack Of Technical Expertise In Complex Algorithm. Notable trends are: Increasing volume of data generated globally and the rising concerns about data breaches, cyber threats, and privacy regulations. .

Market Size, Growth Rate, and Drivers The global data conversion services market is projected to reach a value of $14.16 billion by 2033, growing at a CAGR of 5.48% from 2025 to 2033. The growth is primarily driven by the increasing demand for efficient and accurate data management solutions in various industries, including healthcare, finance, retail, and education. Additionally, the adoption of cloud-based data storage and processing platforms is fueling the demand for data conversion services. Key Trends, Restraints, and Market Segments Key trends in the market include the adoption of artificial intelligence (AI) and machine learning (ML) technologies for automated data conversion, the growing popularity of hybrid conversion methods combining manual and automated processes, and the increasing focus on data privacy and security. Restraints include data integrity concerns and the high cost of data conversion services. The market is segmented based on service type, industry, conversion method, and end user. The major players in the industry include EDataForce, Genpact, Accenture, Data Conversion Services, and HCL Technologies, among others. Key drivers for this market are: Cloud-based data solutions, AI-driven data processing; Real-time data integration; E-commerce data management; Multi-format data handling . Potential restraints include: Data digitization demand, Evolving compliance regulations; Cloud integration growth; Automation adoption trends; Rising data security concerns .

The Higher Education Data Management Service market is experiencing robust growth, driven by the increasing need for efficient data management within educational institutions. The rising adoption of cloud-based solutions, coupled with the expanding use of data analytics for improved decision-making and personalized learning experiences, is fueling market expansion. A projected Compound Annual Growth Rate (CAGR) of, for example, 12% (this is an example, replace with actual or logically estimated CAGR from your data), points to a significant market expansion from an estimated $5 billion in 2025 to potentially over $10 billion by 2033. This growth is further supported by the increasing digitization of higher education processes and the rising demand for advanced data security and compliance solutions. Key players like Ellucian, Oracle, Workday, and Blackboard are actively shaping market dynamics through innovation and strategic partnerships, further driving competition and service enhancements. While the on-premises segment currently holds a substantial market share, cloud-based solutions are rapidly gaining traction due to their scalability, cost-effectiveness, and accessibility. Geographic segmentation reveals that North America currently dominates the market, owing to high technology adoption rates and significant investments in educational infrastructure. However, the Asia-Pacific region is poised for significant growth, fueled by increasing government initiatives promoting digital education and rising student enrollment. Europe also represents a substantial market, driven by technological advancements and a growing demand for efficient data management in higher education institutions. Market restraints include challenges related to data integration across disparate systems, concerns about data security and privacy, and the need for robust IT infrastructure within institutions. Overcoming these challenges through innovative solutions and robust cybersecurity measures will be crucial for sustained market growth in the coming years.

The global point-of-care data management systems market is projected to reach a value of $634.7 million by 2033, expanding at a compound annual growth rate (CAGR) of 12.1% from 2025 to 2033. The market is driven by the increasing adoption of point-of-care testing, the growing demand for real-time patient data, and the need to improve patient safety and efficiency. Key trends include the integration of artificial intelligence (AI) and machine learning (ML) into point-of-care data management systems, the development of cloud-based solutions, and the growing focus on data security and privacy. The key players operating in the market include Siemens, HemoCue, Abbott, Radiometer Medical, Telcor, Thermo Fisher Scientific, Randox Laboratories, Esaote SpA, Hedera Biomedics, Seaward Electronic, and others. Regionally, North America is expected to remain the dominant market throughout the study period, followed by Europe and Asia Pacific. The growth in North America is attributed to the high prevalence of chronic diseases, the well-established healthcare infrastructure, and the favorable reimbursement policies. The market in Asia Pacific is expected to witness the fastest growth during the forecast period due to the rising healthcare expenditure, the increasing demand for affordable healthcare solutions, and the growing adoption of point-of-care testing in remote and underserved areas. This comprehensive report provides an in-depth analysis of the Point-of-Care Data Management Systems market, valued at over $2.5 billion in 2022. It explores the market concentration, product insights, regional trends, and key drivers and challenges shaping the industry.

The Report Covers IoT Data Management Market Forecast and it is segmented by Solution (Integration, Migration, Analytics, Storage, Security), End User (Automotive, Healthcare, Government, Manufacturing, Energy & Utility), and Geography.

The global automotive data management market size was valued at USD 30.06 billion in 2025 and is projected to expand at a CAGR of 8.85% over the forecast period. The growth of the market is attributed to the increasing adoption of connected and autonomous vehicles, the growth of the telematics industry, and the need for efficient data management and analytics. Key drivers of the market include the increasing demand for data-driven insights to improve vehicle performance, safety, and efficiency, the growing adoption of cloud-based data management solutions, and the increasing investment in research and development of new data management technologies. Key trends shaping the market include the adoption of artificial intelligence and machine learning for data analysis, the integration of data management systems with other enterprise applications, and the increasing focus on data security and privacy. Recent developments include: , The Automotive Data Management market is anticipated to witness substantial growth in the coming years., The market is driven by factors such as the increasing adoption of connected cars, the growing need for data security and privacy, and the rising demand for personalized automotive experiences. In 2023, the market was valued at 30.06 billion U.S. dollars and is projected to reach 64.5 billion U.S. dollars by 2032, exhibiting a CAGR of 8.85%. Major players in the market include IBM, SAP, Oracle, and Microsoft., Recent news developments in the market include the launch of new data management solutions by vendors such as IBM and SAP. Additionally, there have been several partnerships and acquisitions in the market, with companies seeking to expand their offerings and gain a competitive advantage., Automotive Data Management Market Segmentation Insights. Key drivers for this market are: Autonomous vehicle development Datadriven vehicle optimization Connected car services Fleet management Customization and personalization. Potential restraints include: Increased vehicle connectivity Growing data volumes Need for data analytics Rising cybersecurity concerns Government regulations.

Global Total Researchers in Data Processing, Hosting and Related Activities; Web Portals by Country, 2023 Discover more data with ReportLinker!

The Big Data Technology Service Market is anticipated to grow exponentially in the coming years, reaching a valuation of 246.07 billion by 2033, with a CAGR of 12.05% from 2025 to 2033. This growth is primarily attributed to the increasing adoption of big data analytics by enterprises across various industry verticals. The vast amount of data generated from various sources, such as social media, IoT devices, and e-commerce platforms, has created a strong demand for solutions that can effectively process, analyze, and manage this data. Several drivers contribute to the market growth, including the rising need for data-driven decision-making, the proliferation of cloud-based services, and the advancements in artificial intelligence and machine learning. Key market trends include the increasing adoption of hybrid and cloud-based big data solutions, the integration of data visualization tools, and the emergence of data marketplaces. However, data security and privacy concerns, lack of skilled professionals, and integration challenges may hinder market growth. The market is segmented based on service type, deployment model, organization size, and industry vertical, with banking, financial services, and insurance (BFSI) being the largest industry vertical due to the increasing adoption of data analytics for risk assessment, fraud detection, and customer segmentation. The key companies in the market include Accenture, Google, Microsoft, Oracle, Teradata, and IBM. Regional analysis reveals that North America holds the largest market share due to the presence of leading technology companies and early adoption of big data analytics solutions. The global big data technology service market is projected to reach $230.1 billion by 2025, expanding at a 12.5% CAGR during the 2020-2025 period. The burgeoning adoption of advanced technologies, such as cloud computing, artificial intelligence (AI), and machine learning (ML), drives market expansion. These technologies facilitate efficient data processing, storage, and analytics, enabling organizations to extract meaningful insights and make informed decisions. Key drivers for this market are: Datadriven decisionmaking Realtime analytics Cloud computing Predictive analytics Risk management. Potential restraints include: Increase in demand for data analytics Rise in adoption of cloudbased services Growing need for realtime data processing.

This statistic illustrates the findings of a 2014 online survey among qualified utility, municipal, commercial and community stakeholders on which areas within their organizations would be best served by increased data management and analytics capabilities. According to 27 percent of respondents, customer billing, collections and or revenue protection is among the top three areas to be served by such services.