The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature. The current version of the database expands its coverage to about 180 countries for 45 years, 1975-2020. It has become one of the most cited databases in comparative political economy and comparative political institutions, with more than 4,500 article citations on Google Scholar as of December 2020.

Graph and download economic data for Disposable Personal Income (DPI) from Q1 1947 to Q1 2025 about disposable, personal income, personal, income, GDP, and USA.

United States Disposable Personal Income (DPI) data was reported at 8,270.418 USD bn in Oct 2003. This records an increase from the previous number of 8,238.870 USD bn for Sep 2003. United States Disposable Personal Income (DPI) data is updated monthly, averaging 2,208.658 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 8,319.767 USD bn in Aug 2003 and a record low of 341.441 USD bn in Jan 1959. United States Disposable Personal Income (DPI) data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

This dataset includes point location data for public schools in Wisconsin. The points are placed on or near each school building's centroid. Out of the 2,277 schools listed in the attribute table, 2,152 have a physical location while 125 are completely virtual campuses. School data was pulled from the Department of Public Instruction's schools database on January 17, 2025. This data gets updated biannually so for more up-to-date information, please visit the DPI public school directory.

Database that provides users with information on protein-protein interactions, as well as experimental and inferring interactions, for the organism Helicobacter pylori. Searching the database provides users with the ORF, locus, similarity comparisons, and description for the object queried.

Enrollment is a head count of all students receiving their primary PK-12 educational services through Wisconsin public schools. This map is in a series of maps that show enrollments by district for a particular student group (demographic) for the 2023-2024 school year. Additional enrollment data are available for the public to view on the WISEdash Public Portal. Enrollment data is sourced from the WISEdata system. Enrollment Count is the number of students enrolled on specific dates as determined by school enrollment/exit dates that cover those dates. Percent Enrollment by Student Group is a percent of the enrollment count for all student groups combined. DPI collects data to meet all required school, district, state, and federal reporting mandates, e.g., Every Student Succeeds Act (ESSA), Individuals with Disabilities Education Act (IDEA), and Title II Higher Education Act. These data inform education research and data analysis. Multiple teams from IT and content areas work together at DPI to build tools for data collection, to support districts in data collection, and to report on and facilitate the use of data based on federal and state reporting mandates. Through the DPI dashboard and reporting tools, DPI staff, teachers, administrators, parents, and researchers are better able to understand and improve educational outcomes for Wisconsin students.A person's race or ethnicity is the racial and/or ethnic group to which the person belongs or with which he or she most identifies. Ethnicity is self-reported as either Hispanic/Not Hispanic. Race is self-reported as any of the following 5 categories: Asian, American Indian or Alaskan Native, Black or African American, Native Hawaiian or other Pacific Islander, or White. The data displayed reflects the race/ethnicity that is reported by school districts to DPI.An economically disadvantaged student is one who is identified by Direct Certification (only if participating in the National School Lunch Program) OR a member of a household that meets the income eligibility guidelines for free or reduced-price meals (less than or equal to 185 percent of Federal Poverty Guidelines) under the National School Lunch Program (NSLP) OR identified by an alternate mechanism, such as the alternate household income form.English Learner status is any student whose first language, or whose parents' or guardians' first language, is not English and whose level of English proficiency requires specially designed instruction, either in English or in the first language or both, in order for the student to fully benefit from classroom instruction and to be successful in attaining the state's high academic standards expected of all students at their grade level.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Deep Packet Inspection (DPI) Market Outlook

The global Deep Packet Inspection (DPI) market size is projected to grow significantly from USD 11 billion in 2023 to approximately USD 24 billion by 2032, exhibiting a compound annual growth rate (CAGR) of around 9.3%. This robust growth trajectory is primarily driven by the increasing need for network security and data protection in an era of escalating cyber threats and expanding data consumption. The demand for DPI solutions and services is being bolstered by the growing sophistication of cyber-attacks and the ever-increasing volume of networked data, compelling organizations across various sectors to enhance their data inspection capabilities.

A pivotal growth factor in the DPI market is the proliferation of network traffic due to the exponential rise in internet usage, streaming services, and connected devices. As networks become more complex and data volumes surge, the traditional forms of packet inspection become inadequate, necessitating advanced DPI solutions that can scrutinize data packets more deeply and effectively. This has led to significant investments in developing sophisticated DPI technologies capable of handling high-speed data transfer while maintaining robust security. Moreover, the advent of 5G and IoT technologies is expected to further fuel DPI market growth by creating an unprecedented demand for network management and security solutions.

Another critical factor contributing to the DPI market’s expansion is the increasing regulatory requirements and compliance mandates across various industries. Governments and regulatory bodies around the world are enforcing stringent data protection laws that necessitate the implementation of advanced network security measures, including DPI. These regulations not only drive the adoption of DPI solutions but also encourage continuous innovation in this space to meet ever-changing compliance requirements. Furthermore, organizations seeking to protect their brand integrity and customer trust are increasingly adopting DPI as part of a comprehensive cybersecurity strategy, which further propels market growth.

The DPI market is also witnessing growth due to advancements in artificial intelligence (AI) and machine learning (ML), which are being integrated into DPI solutions to enhance their efficiency and accuracy. AI and ML technologies enable DPI systems to identify and respond to threats more swiftly by learning from data patterns and predicting potential anomalies. This integration of AI into DPI tools helps organizations stay ahead of sophisticated attacks, thus driving up the demand for next-generation DPI solutions. Additionally, the cost-effectiveness and scalability of cloud-based DPI solutions have made them increasingly attractive to businesses of all sizes, further contributing to market growth.

Regionally, North America is expected to maintain its dominance in the DPI market due to the early adoption of advanced technologies and the presence of major market players. However, the Asia Pacific region is anticipated to exhibit the highest growth rate, driven by rapid digitalization, increasing internet penetration, and growing awareness of cybersecurity threats. The expansion of telecommunications infrastructure in emerging economies within the Asia Pacific is also a significant catalyst for DPI market growth in this region, presenting lucrative opportunities for vendors and service providers.

Component Analysis

In the DPI market, components are divided into two major categories: Solutions and Services. The solutions segment encompasses the various DPI software and hardware offerings that are designed to provide comprehensive network traffic analysis, intrusion detection, and data protection. As organizations increasingly recognize the importance of robust network security, the demand for DPI solutions is on the rise. This segment is characterized by a wide range of offerings, from basic DPI tools to advanced integrated solutions that provide real-time analytics and threat detection. The need for comprehensive solutions that can handle diverse network environments and traffic patterns is driving innovation and competition in this segment.

The services segment, on the other hand, involves professional services such as consulting, integration, maintenance, and support. As DPI solutions become more sophisticated, organizations often require expert guidance to implement and optimize these systems effectively. This has led to a growing demand for DPI-related services, particularly in sectors that lack in-house expertise in network security. Service providers

Factor 1: Internet Speed; Factor 2: Internet Users; Factor 3: Hardware; Factor 4: Mobile Devices; Factor 5: Education. Remark: the number of samples (countries with complete datasets) is 152.Statistical assessment of the DPI factors.

• Since mid-2015 the netindex.com website is no longer accessible; however an alternative source of Internet Speed data is: http://www.ookla.com.Weblinks for data sources used for the DPI factors.

Deep Packet Inspection (DPI) Market size was valued at USD 31.2 Billion in 2024 and is projected to reach USD 156.7 Billion by 2032, growing at a CAGR of 24.61% from 2026 to 2032.

Global Deep Packet Inspection (DPI) Market Drivers

Network Security: DPI is crucial for detecting and preventing various network threats, including malware, viruses, and unauthorized access.

Network Optimization: DPI can help optimize network performance by identifying and addressing bottlenecks, improving network efficiency.

Quality of Service (QoS): DPI enables network operators to prioritize traffic and ensure that critical applications receive the necessary bandwidth.

Global Deep Packet Inspection (DPI) Market Restraints

Performance Overhead: DPI can introduce performance overhead, especially when inspecting large volumes of traffic.

Complexity: Implementing and managing DPI solutions can be complex, requiring specialized skills and expertise.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Overview of the average DPI factor scores compared to the World Bank income classification.

Rice agronomy field experiment results data. Different seasons, sites, sowing methods, nitrogen treatments and varieties.

Customs records of France are available for AMIN DPI. Learn about its Importer, supply capabilities and the countries to which it supplies goods

Replicated trials at two locations. Three water and four nitrogen treatments. Soil sample data gravimetric moisture, chemical properties.

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Apr 2025 about disposable, personal income, personal, income, real, and USA.

Data published by the Department of Primary Industries (DPI) that supports the Digital Projects Dashboard. Data resources include the list of digital and information and communication technology (ICT) enabled initiatives and their reported status. For further information, visit the Queensland Government Digital Projects Dashboard website. Please refer to the pages: About the dashboard, FAQs and Glossary.

The Deep Packet Inspection (DPI) tool market is experiencing robust growth, driven by the increasing need for network security and optimization across various sectors. The market's expansion is fueled by the rising adoption of cloud-based applications, the proliferation of IoT devices generating vast amounts of network traffic, and the escalating concerns surrounding data breaches and cyber threats. Large enterprises are leading the adoption, investing heavily in sophisticated DPI solutions to manage and secure their complex networks. However, SMEs are also increasingly adopting these tools as they become more affordable and user-friendly, driven by a growing awareness of the potential risks associated with unmonitored network traffic. The market is segmented by deployment type (cloud-based and on-premises), with cloud-based solutions gaining significant traction due to their scalability, cost-effectiveness, and ease of management. North America and Europe currently hold a significant market share, owing to the advanced technological infrastructure and stringent data privacy regulations in these regions. However, the Asia-Pacific region is projected to witness the fastest growth rate in the coming years, driven by rapid digitalization and expanding internet penetration. While the market faces restraints such as high implementation costs and the complexity of managing DPI solutions, the overall outlook remains positive, with considerable growth potential predicted throughout the forecast period (2025-2033). The competitive landscape is characterized by a mix of established players and emerging startups. Established vendors like ManageEngine, SolarWinds, and Netscout offer comprehensive DPI solutions catering to large enterprises, while smaller companies are focusing on niche applications or specific functionalities. The market is witnessing continuous innovation with the development of advanced DPI techniques capable of handling encrypted traffic and emerging network protocols. Future growth will be fueled by advancements in artificial intelligence and machine learning, enabling more accurate threat detection and efficient network optimization. The integration of DPI with other security solutions, such as intrusion detection systems and firewalls, will further enhance its value proposition. The increasing adoption of 5G networks will also drive demand, requiring advanced DPI capabilities to manage the increased bandwidth and data volume. Overall, the DPI tool market shows a promising trajectory, poised for significant growth due to its critical role in maintaining network security and performance in an increasingly interconnected world.

Abstract

This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. Metadata was not provided and has been compiled by the Bioregional Assessment Programme based on known details at the time of acquisition.

Vegetation in NSW of high ecological value having high probability of being groundwater dependent were identified through a process that used current vegetation data, depth to groundwater data, data that showed potential frequency of water use other than surface water based on a continuous 10 year period and expert opinion. High Probability vegetation communities were identified as being of High Ecological Value when they sat within one or more selected datasets. (see below) Geographic Extent: Hunter & Central Rivers CMA

This is a preliminary dataset, the project is on going.

This dataset has been provided to the BA Programme on the condition that third parties may not reproduce this dataset. Third parties wishing to use or reproduce this data should contact the data provider.

Purpose

Note this dataset is a draft pre-release for use in the Bioregional Assessment Programme. This dataset is not to be published in BA until the data provider releases the data on their website.

Dataset History

Data Quality:

Data sources:

High Probability

1. Vegetation: obtained from OEH

2. Depth to groundwater: modelled data provided by Office of Water Hydrogeologists

3. Potential frequency of water use other than surface water based on a continuous 10

year period : This data set was created by Herbert Hemakumara (Office of Water) using

remote sensing MODIS

High Ecological Value

1. National Parks and State Forests (OEH)

2. SEPP 14 & 26 (Dept Planning)

3. RAMSAR Wetlands (OEH)

4. Marine parks and aquatic reserves (OEH)

5. Identified rain forest communities (OEH)

6. Threatened or endangered species (OEH)

7. Wildlife corridors, Regional Conservation strategies or communities identified as

being significant in various studies (Various Sources)

Dataset Citation

NSW Office of Water (2015) Hunter CMA GDEs (DRAFT DPI pre-release). Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/469d6d2e-900f-47a7-a137-946b89b3d188.