Unlock valuable salary insights with our comprehensive Salary Dataset, designed for businesses, recruiters, and job seekers to analyze compensation trends, workforce planning, and market competitiveness.

Dataset Features

Job Listings & Salaries: Access structured salary data from top job platforms, including job titles, company names, locations, salary ranges, and compensation types. Employer & Industry Insights: Extract company-specific salary trends, industry benchmarks, and hiring patterns. Geographic Pay Disparities: Compare salaries across different regions, cities, and countries to identify location-based compensation trends. Job Market Trends: Monitor salary fluctuations, demand for specific roles, and hiring trends over time.

Customizable Subsets for Specific Needs Our Salary Dataset is fully customizable, allowing you to filter data based on job titles, industries, locations, experience levels, and salary ranges. Whether you need broad market insights or focused data for recruitment strategy, we tailor the dataset to your needs.

Popular Use Cases

Workforce Planning & Talent Acquisition: Optimize hiring strategies by analyzing salary benchmarks and compensation trends. Market Research & Competitive Intelligence: Compare salaries across industries and competitors to stay ahead in talent acquisition. Career Decision-Making: Help job seekers evaluate salary expectations and identify high-paying opportunities. AI & Predictive Analytics: Use structured salary data to train AI models for job market forecasting and compensation analysis. Geographic Expansion & Business Strategy: Assess salary variations across regions to plan business expansions and remote workforce strategies.

Whether you're optimizing recruitment, analyzing salary trends, or making data-driven career decisions, our Salary Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

1) Data Introduction • The Data Science Salaries 2023 Dataset is a global annual salary analysis dataset that summarizes a variety of information in a tabular format, including salary, career, employment type, job, remote work rate, and company location and size for data science jobs as of 2023.

2) Data Utilization (1) Data Science Salaries 2023 Dataset has characteristics that: • Each row contains 11 key characteristics, including year, career level, employment type, job name, annual salary (local currency and USD), employee country of residence, remote work rate, company location, and company size. • Data is organized to reflect different countries, jobs, careers, and work patterns to analyze pay and work environments in data science in three dimensions. (2) Data Science Salaries 2023 Dataset can be used to: • Data Science Salary Analysis and Comparison: Analyzing salary levels and distributions by job, career, country, and company size can be used to understand industry trends and market value. • Establishing Recruitment and Career Strategies: It can be applied to recruitment strategies, career development, global talent attraction, etc. by analyzing the correlation between various working conditions and salaries such as remote work rates, employment types, and company location.

Context

An anonymous salary survey has been conducted annually since 2015 among European IT specialists with a stronger focus on Germany. This year 1238 respondents volunteered to participate in the survey. The data has been made publicly available by the authors. The dataset contains rich information about the salary patterns among the IT professionals in the EU region and offers some great insights.

An accompanying article - IT Salary Survey December 2020 has also been published which goes deeper into the findings.

Acknowledgements 🙏🏻

Thanks to Ksenia Legostay for curating and analyzing the data. Additional thanks to Viktor Shcherban and Sergey Vasilyev for collaborating on the survey.

The global salary benchmarking software market is experiencing robust growth, driven by increasing demand for accurate and efficient compensation management solutions across diverse industries. The market's expansion is fueled by several factors, including the need for competitive compensation strategies to attract and retain top talent in a tight labor market, the growing adoption of cloud-based solutions for enhanced accessibility and scalability, and the increasing regulatory scrutiny around pay equity and transparency. Companies are increasingly leveraging these software solutions to analyze salary data, identify pay gaps, and ensure fair compensation practices, leading to improved employee morale and reduced turnover. The market is segmented by deployment type (cloud-based and on-premise), organizational size (small, medium, and large enterprises), and industry vertical. While precise figures are unavailable, a reasonable estimate based on industry analysis and considering a relatively high CAGR (let's assume a CAGR of 15% for illustration purposes), suggests a 2025 market size of approximately $2 billion, with projections indicating continued substantial growth through 2033. This projection incorporates the expected expansion of the user base and increasing feature complexity within the software. The competitive landscape is characterized by a blend of established players and emerging startups. Established players like Workday and Carta Total Comp benefit from strong brand recognition and extensive client networks. Newer entrants, including MarketPay and OpenComp, are disrupting the market with innovative features and agile approaches. Market consolidation through mergers and acquisitions is likely, given the ongoing technological advancements and the increasing demand for integrated HR solutions. However, challenges persist. High implementation costs, integration complexities with existing HR systems, and concerns about data security can hinder market penetration. The future success of vendors will hinge on their ability to offer user-friendly interfaces, robust data analytics capabilities, and cost-effective solutions tailored to the specific needs of different customer segments. Furthermore, continuous innovation to incorporate AI-driven features for predictive analysis and compensation optimization will become crucial for gaining a competitive edge.

Dataset Description

Overview: This collection features two distinct datasets, offering a detailed view of Data Science and Analytics job opportunities in Australia for 2024. Derived from Glassdoor, these datasets provide a comprehensive overview of the current trends, demands, and openings in the data-focused job market in Australia.

Data Science Applications: With nearly 670 records combined, these datasets are ideal for conducting job market trend analysis, understanding skill requirements, and benchmarking salaries within the Australian data science and analytics sectors. They are invaluable for market research, career guidance, educational program adjustments, and strategic planning in alignment with industry evolution.

Column Descriptors: - Company Name: The employing organization. - Job Title: The designated position. - Job Description: A summary of job responsibilities and requirements. - Location: City and Country of the job posting. - Salary Information: Details on salary estimates and pay periods. - Job Posted Date: The date when the job was made public.

Ethically Mined Data: The information within these datasets has been responsibly collected, maintaining adherence to data privacy and protection regulations, ensuring ethical integrity.

Acknowledgements: Thanks are due to Glassdoor for its role as a key source, offering transparent insights into the job market. The creative input of Dall-E 3 in producing the dataset's accompanying imagery is also recognized, enhancing the datasets' presentation.

Final Thoughts: These datasets aim to support a nuanced understanding of the data science and analytics job landscape in Australia, facilitating informed decision-making for professionals, educators, and students in the field.

Snapshot img

Compensation Software Market Size 2025-2029

The compensation software market size is forecast to increase by USD 7.83 billion, at a CAGR of 11.6% between 2024 and 2029.

The market is driven by the increasing adoption of pricing strategies by companies in response to the growing demand for integrated Human Capital Management (HCM) solutions. This trend reflects the evolving needs of businesses seeking to streamline their HR processes and gain a competitive edge through data-driven compensation decisions. However, high implementation and maintenance costs pose a significant challenge for market participants. These expenses can deter smaller organizations and limit the market's growth potential. To capitalize on opportunities and navigate challenges effectively, companies must focus on offering cost-effective solutions while maintaining the necessary functionality and integration capabilities.
By addressing the cost concern, companies can expand their customer base and strengthen their market position. Additionally, continuous innovation and investment in technology will be crucial to meet the evolving demands of businesses and maintain a competitive edge.

What will be the Size of the Compensation Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by the dynamic nature of business environments and the need for innovative solutions. Seamlessly integrated offerings, such as API integrations, machine learning, reporting and dashboards, HRS integration, deferred compensation, compensation procedures, variable pay, compensation reviews, real-time data, compensation design, security and compliance, incentive programs, mobile compensation, and performance management, are essential for organizations to effectively manage their talent and rewards strategies. Compensation software solutions are increasingly being adopted across various sectors to streamline processes, ensure compliance, and optimize costs. These solutions enable organizations to design and implement compensation strategies, policies, and philosophies that align with their business objectives.

Data visualization and analytics are critical components of compensation software, providing valuable insights into compensation trends and patterns. Machine learning algorithms and predictive analytics enable organizations to make data-driven decisions, optimize compensation structures, and retain top talent. Security and compliance are paramount in the market. Solutions must adhere to the latest regulations and standards to ensure data privacy and security. Integrations with HRIS, payroll, benefits administration, and performance management systems further enhance the functionality of compensation software. Compensation software solutions offer user-friendly interfaces, enabling easy access to critical information. Real-time data and automated workflows enable organizations to make timely compensation adjustments and respond to market changes.

Incentive programs, bonuses, and performance-based pay are essential components of compensation software, enabling organizations to align employee compensation with performance and business objectives. Employee engagement, satisfaction, and development are also key areas of focus, with solutions offering training, career pathing, and communication tools. Budgeting and forecasting capabilities enable organizations to optimize costs and plan for future compensation needs. Cloud-based solutions offer flexibility and scalability, while workflow automation streamlines processes and improves efficiency. Compensation software solutions continue to evolve, with new features and capabilities emerging to meet the changing needs of organizations. The market is expected to remain dynamic, with ongoing innovation and competition driving growth and development.

How is this Compensation Software Industry segmented?

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

End-user

  Large enterprises
  SMEs


Deployment

  Cloud-based
  On-premises


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By End-user Insights

The large enterprises segment is estimated to witness significant growth during the forecast period.

In the dynamic business landscape, compensation software solutions have emerged as essential tools for managing intricate compensation strategies and policies. Large enterprises dominate the mark

The Payroll & Compensation Management Market report segments the industry into Type (Software, Services), Application (Payroll, Employee Benefits, and more), Deployment (On-Premises Deployment, Cloud Hosted Deployment), End-User Industry (BFSI, Retail, and more), and Region (North America, Europe, and more).

The primary purpose of this survey is to collect data on the salaries, tenure, and fringe benefits of full-time instructional faculty by contract length, sex, and academic rank. These data permit analysis, from a national perspective, of the number and tenure status of full-time faculty members in relation to enrollment and number of degrees granted, and the evaluation of faculty compensation in relation to institutional financial resources for an indication of the economic status of institutions. These data also enable trend analysis of average full-time salaries for an assessment of the economic status of full-time faculty. Part 1, Response Status Information, contains response status information to the salary and fringe benefits survey for active institutions in the final universe. Part 2, Salaries and Tenure of Full-Time Instructional Faculty, contains salary and tenure data. Salary data include total salary outlays and the total number of instructional faculty that were paid those outlays. Tenure data include number of faculty with tenure, number on tenure track, and number not on tenure track. Part 3, Fringe Benefits of Full-Time Instructional Faculty, contains benefits data. Benefits data include fringe benefit expenditures and the number of full-time faculty covered by retirement, medical/dental, and group life insurance plans. (Source: ICPSER, retrieved 07/19/2011

About this dataset

Context

The dataset tabulates the median household income in Gold Beach. It can be utilized to understand the trend in median household income and to analyze the income distribution in Gold Beach by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Gold Beach, OR Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Gold Beach, OR: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Gold Beach, OR
• Gold Beach, OR households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Gold Beach median household income. You can refer the same here

The Disability Income Protection Insurance market plays a crucial role in safeguarding individuals against the financial hardships that can arise from unexpected work interruptions due to illness or injury. This type of insurance ensures that policyholders receive a portion of their income when they are unable to pe

The Flight Missed Connection Compensation Service market has emerged as a vital segment within the travel industry, especially as air travel becomes increasingly complex. With millions of passengers traveling through airports globally, flight disruptions can lead to significant inconveniences, including missed conne

About this dataset

Context

The dataset tabulates the median household income in Pinedale. It can be utilized to understand the trend in median household income and to analyze the income distribution in Pinedale by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Pinedale, WY Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Pinedale, WY: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Pinedale, WY
• Pinedale, WY households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Pinedale median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Rush Springs. It can be utilized to understand the trend in median household income and to analyze the income distribution in Rush Springs by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Rush Springs, OK Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Rush Springs, OK: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Rush Springs, OK
• Rush Springs, OK households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Rush Springs median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Schwenksville. It can be utilized to understand the trend in median household income and to analyze the income distribution in Schwenksville by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Schwenksville, PA Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Schwenksville, PA: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Schwenksville, PA
• Schwenksville, PA households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Schwenksville median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Ramona. It can be utilized to understand the trend in median household income and to analyze the income distribution in Ramona by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Ramona, OK Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Ramona, OK: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Ramona, OK
• Ramona, OK households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Ramona median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Fresno. It can be utilized to understand the trend in median household income and to analyze the income distribution in Fresno by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Fresno, CA Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Fresno, CA: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Fresno, CA
• Fresno, CA households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Fresno median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Croghan. It can be utilized to understand the trend in median household income and to analyze the income distribution in Croghan by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Croghan, NY Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Croghan, NY: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Croghan, NY
• Croghan, NY households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Croghan median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Rush Valley. It can be utilized to understand the trend in median household income and to analyze the income distribution in Rush Valley by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Rush Valley, UT Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Rush Valley, UT: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Rush Valley, UT
• Rush Valley, UT households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Rush Valley median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Jones County. It can be utilized to understand the trend in median household income and to analyze the income distribution in Jones County by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Jones County, IA Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Jones County, IA: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Jones County, IA
• Jones County, IA households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Jones County median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Dolores. It can be utilized to understand the trend in median household income and to analyze the income distribution in Dolores by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Dolores, CO Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Dolores, CO: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Dolores, CO
• Dolores, CO households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Dolores median household income. You can refer the same here