The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

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shots2000s.csv - - Data from 2000-01 season through 2009-10 season

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About this dataset

Context

The dataset tabulates the population of Great Valley town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Great Valley town. The dataset can be utilized to understand the population distribution of Great Valley town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Great Valley town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Great Valley town.

Key observations

Largest age group (population): Male # 5-9 years (96) | Female # 60-64 years (136). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Great Valley town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Great Valley town is shown in the following column.
• Population (Female): The female population in the Great Valley town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Great Valley town for each age group.

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/.

Recommended for further research

This dataset is a part of the main dataset for Great Valley town Population by Gender. You can refer the same here

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The statistic shows the cumulative revenues from the ten leading artificial intelligence (AI) use cases worldwide, between 2016 and 2025. Over the ten years between 2016 and 2025, AI software for vehicular object detection, identification, and avoidance is expected to generate * billion U.S. dollars.

Introduction

Gesture Recognition Statistics: Gesture recognition is a subfield of computer vision and human-computer interaction that interprets human gestures using algorithms, with applications in gaming, virtual reality, robotics, and assistive devices.

Gestures are categorized into static and dynamic types, with recognition methods. Including vision-based techniques (2D and 3D) and sensor-based approaches utilizing wearable devices.

Challenges such as gesture variability, environmental factors, and the need for real-time processing must be addressed for effective recognition.

Further, this technology has diverse applications, from enhancing gaming experiences to facilitating smart home controls and improving human-robot interaction.

Future trends point toward improved AI algorithms, integration with other technologies, and increased use of wearable gesture recognition systems.

These are the key social media statistics that you need to know.

Context

The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

Content

Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

Update Frequency: Monthly

Querying BigQuery Tables

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Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

Dataset Source: http://www.bls.gov/data/

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Clark Young from Unsplash.

Inspiration

What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

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VetPop2023 top 10 states where Veterans reside in fiscal year 2024

This dataset ranks the top 10 UK coffee shop, café, and dessert parlour brands based on forecasted outlet numbers as of December 2025. It provides a snapshot of market presence by brand and highlights the leading players in the out-of-home coffee and dessert sectors.