Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

PA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 0.837 Number in 2016. This records an increase from the previous number of 0.667 Number for 2015. PA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 0.652 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 0.847 Number in 2014 and a record low of 0.245 Number in 2006. PA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data was reported at 27.240 USD in May 2018. This records an increase from the previous number of 27.090 USD for Apr 2018. Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data is updated monthly, averaging 23.010 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 27.240 USD in May 2018 and a record low of 19.250 USD in Mar 2006. Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G033: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Seasonally Adjusted.

Our most comprehensive database of AI models, containing over 800 models that are state of the art, highly cited, or otherwise historically notable. It tracks key factors driving machine learning progress and includes over 300 training compute estimates.

ZM: Domestic General Government Health Expenditure: % of Current Health Expenditure data was reported at 36.560 % in 2015. This records an increase from the previous number of 31.720 % for 2014. ZM: Domestic General Government Health Expenditure: % of Current Health Expenditure data is updated yearly, averaging 27.533 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 36.560 % in 2015 and a record low of 8.458 % in 2009. ZM: Domestic General Government Health Expenditure: % of Current Health Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Health Statistics. Share of current health expenditures funded from domestic public sources for health. Domestic public sources include domestic revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, non-profit institutions serving households (NPISH) or enterprise financing schemes as well as compulsory prepayment and social health insurance contributions. They do not include external resources spent by governments on health.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

The Database Security market is experiencing robust growth, projected to reach $2556.1 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 11.4% from 2025 to 2033. This expansion is fueled by the increasing frequency and sophistication of cyberattacks targeting sensitive data stored in databases, coupled with stringent data privacy regulations like GDPR and CCPA. The rising adoption of cloud computing and the proliferation of big data also contribute significantly to market growth, as organizations require robust security solutions to protect their valuable data assets across diverse environments. The market is segmented by application (SMEs, Large Enterprises) and type (Marketing, Sales, Operations, Finance, HR & Legal), with large enterprises and applications involving sensitive financial data demonstrating particularly high demand for advanced database security solutions. North America currently holds a dominant market share due to early adoption of advanced technologies and a strong regulatory landscape, but the Asia-Pacific region is poised for significant growth, driven by increasing digitalization and a rapidly expanding economy. The competitive landscape is characterized by a mix of established players like Oracle and IBM, alongside specialized security vendors such as Trustwave and McAfee. These companies offer a wide range of solutions, including database activity monitoring, encryption, access control, and vulnerability management. The market is witnessing innovation in areas like AI-powered threat detection and automated security response, which are enhancing the effectiveness and efficiency of database security solutions. However, challenges remain, including the rising complexity of cyber threats, the skills gap in cybersecurity professionals, and the high cost of implementing and maintaining comprehensive database security systems. The continued evolution of cyberattacks and data privacy regulations will be key drivers shaping the future of this dynamic market.

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

According to Cognitive Market Research, the global In-Memory Database market size will be USD 7.8 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 19.1% from 2024 to 2031. Market Dynamics of In-Memory Database Market

Key Drivers for In-Memory Database Market

Increasing Volume of Data - The exponential growth of data generated by various sources, including social media, IoT devices, and enterprise applications, is another key driver for the IMDB market. Organizations are increasingly seeking efficient ways to manage and analyze this vast amount of data to gain actionable insights and maintain a competitive edge. In-memory databases are well-suited to handle large volumes of data with high throughput, providing the scalability needed to accommodate the growing data influx. The ability to scale horizontally by adding more nodes to the database cluster ensures that IMDBs can meet the demands of data-intensive applications.
The increasing dependence on real-time analytics and decision-making is anticipated to drive the In-Memory Database market's expansion in the years ahead.

Key Restraints for In-Memory Database Market

The amount of available RAM, which can restrict their scalability for very large datasets, limits the In-Memory Database industry growth.
The market also faces significant difficulties related to the high cost of implementation.

Introduction of the In-Memory Database Market

The In-Memory Database market is experiencing robust growth, driven by the need for high-speed data processing and real-time analytics across various industries. In-memory databases store data directly in the main memory (RAM) rather than on traditional disk storage, allowing for significantly faster data retrieval and manipulation. This technology is particularly advantageous for applications requiring rapid transaction processing and real-time data insights, such as financial services, telecommunications, and e-commerce. Despite its benefits, the market faces challenges, including high implementation costs and limitations on data storage capacity due to RAM constraints. Additionally, concerns about data volatility and the need for continuous power supply further complicate adoption. However, advancements in memory technology, declining costs of RAM, and the increasing demand for real-time analytics are driving market growth. As businesses seek to enhance performance and decision-making capabilities, the In-Memory Database market is poised for continued expansion, providing critical solutions for high-performance data management.

Data Entry Service Market Outlook

The global data entry service market size is poised to experience significant growth, with the market expected to rise from USD 2.5 billion in 2023 to USD 4.8 billion by 2032, achieving a Compound Annual Growth Rate (CAGR) of 7.5% over the forecast period. This growth can be attributed to several factors including the increasing adoption of digital technologies, the rising demand for data accuracy and integrity, and the need for businesses to manage vast amounts of data efficiently.

One of the key growth factors driving the data entry service market is the rapid digital transformation across various industries. As businesses continue to digitize their operations, the volume of data generated has increased exponentially. This data needs to be accurately entered, processed, and managed to derive meaningful insights. The demand for data entry services has surged as companies seek to outsource these non-core activities, enabling them to focus on their primary business operations. Additionally, the widespread adoption of cloud-based solutions and big data analytics has further fueled the demand for efficient data management services.

Another significant driver of market growth is the increasing need for data accuracy and integrity. Inaccurate or incomplete data can lead to poor decision-making, financial losses, and a decrease in operational efficiency. Organizations are increasingly recognizing the importance of maintaining high-quality data and are investing in data entry services to ensure that their databases are accurate, up-to-date, and reliable. This is particularly crucial for industries such as healthcare, BFSI, and retail, where precise data is essential for regulatory compliance, customer relationship management, and operational efficiency.

The cost-effectiveness of outsourcing data entry services is also contributing to market growth. By outsourcing these tasks to specialized service providers, organizations can save on labor costs, reduce operational expenses, and improve productivity. Service providers often have access to advanced tools and technologies, as well as skilled professionals who can perform data entry tasks more efficiently and accurately. This not only leads to cost savings but also allows businesses to reallocate resources to more strategic activities, driving overall growth.

From a regional perspective, the Asia Pacific region is expected to witness the highest growth in the data entry service market during the forecast period. This can be attributed to the region's strong IT infrastructure, the presence of numerous outsourcing service providers, and the growing adoption of digital technologies across various industries. North America and Europe are also significant markets, driven by the high demand for data management services in sectors such as healthcare, BFSI, and retail. The Middle East & Africa and Latin America are anticipated to experience steady growth, supported by increasing investments in digital infrastructure and the rising awareness of the benefits of data entry services.

Service Type Analysis

The data entry service market can be segmented into various service types, including online data entry, offline data entry, data processing, data conversion, data cleansing, and others. Each of these service types plays a crucial role in ensuring the accuracy, integrity, and usability of data. Online data entry services involve entering data directly into an online system or database, which is essential for real-time data management and accessibility. This service type is particularly popular in industries such as e-commerce, where timely and accurate data entry is critical for inventory management and customer service.

Offline data entry services, on the other hand, involve entering data into offline systems or databases, which are later synchronized with online systems. This service type is often used in industries where internet connectivity may be unreliable or where data security is a primary concern. Offline data entry is also essential for processing historical data or data that is collected through physical forms and documents. The demand for offline data entry services is driven by the need for accurate and timely data entry in sectors such as manufacturing, government, and healthcare.

Data processing services involve the manipulation, transformation, and analysis of raw data to produce meaningful information. This includes tasks such as data validation, data sorting, data aggregation, and data analysis. Data processing is a critical componen

Data set consists of daily logs by menhaden purse-seine vessels w/ data on individual purse-seine set size, location, and date

Reproducibility data for the AntiBody Sequence Database (ABSD) article. This dataset contains the raw data (antibody sequences) extracted on June 20, 2024, from various databases, as well as the several scripts, to ensure the reproducibility of our results. External databases used: ABDB, AbPDB, CoV-AbDab, Genbank, IMGT, PDB, SACS, SAbDab, TheraSAbDab, UniProt, KABAT Scripts usage: each external database has a corresponding script to format all antibody sequences extracted from it. A last script enable merging all extracted antibody sequences while removing redundancy, standardizing and cleaning data.

Information for how to cite the MTE bundle.

Systematization and classification of carbohydrates contribute greatly to development of modern biomedical sciences. CCSD (CarbBank) data constitute the significant part of nearly all existing carbohydrate databases. However, these data have not been verified from their original deposit. During the expansion of Bacterial Carbohydrate Structure Database (BCSDB) project, we checked CCSD data quality and found that about 35% of records contained errors. The CCSD data cannot be used without manual verification, while CCSD errors migrate from database to database.

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This study uses historical records from 36 archives in the United States to analyze 8,437 enslaved people's sale and/or appraisal prices from 1797 to 1865.

The King County Groundwater Protection Program maintains a database of groundwater wells, water quality and water level sampling data. Users may search the database using Quick or Advanced Search OR use King County Groundwater iMap map set. The viewer provides a searchable map interface for locating groundwater well data.