Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 1.

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The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification.

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The variables for part 2 of the dataset are:

• Individual home ownership for the census usually resident population count aged 15 years and over
• Usual residence 1 year ago indicator
• Usual residence 5 years ago indicator
• Years at usual residence
• Average years at usual residence
• Years since arrival in New Zealand for the overseas-born census usually resident population count
• Average years since arrival in New Zealand for the overseas-born census usually resident population count
• Study participation
• Main means of travel to education, by usual residence address for the census usually resident population who are studying
• Main means of travel to education, by education address for the census usually resident population who are studying
• Highest qualification for the census usually resident population count aged 15 years and over
• Post-school qualification in New Zealand indicator for the census usually resident population count aged 15 years and over
• Highest secondary school qualification for the census usually resident population count aged 15 years and over
• Post-school qualification level of attainment for the census usually resident population count aged 15 years and over
• Sources of personal income (total responses) for the census usually resident population count aged 15 years and over
• Total personal income for the census usually resident population count aged 15 years and over
• Median ($) total personal income for the census usually resident population count aged 15 years and over
• Work and labour force status for the census usually resident population count aged 15 years and over
• Job search methods (total responses) for the unemployed census usually resident population count aged 15 years and over
• Status in employment for the employed census usually resident population count aged 15 years and over
• Unpaid activities (total responses) for the census usually resident population count aged 15 years and over
• Hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Average hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Industry, by usual residence address for the employed census usually resident population count aged 15 years and over
• Industry, by workplace address for the employed census usually resident population count aged 15 years and over
• Occupation, by usual residence address for the employed census usually resident population count aged 15 years and over
• Occupation, by workplace address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by usual residence address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by workplace address for the employed census usually resident population count aged 15 years and over
• Sector of ownership for the employed census usually resident population count aged 15 years and over
• Individual unit data source.

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Download lookup file for part 2 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value

Comprehensive dataset of 11 State Department of Tourisms in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Dataset shows an individual’s statistical area 2 (SA2) of usual residence and the SA2 of their place of study, for the census usually resident population count who are studying (part time or full time), by main means of travel to education from the 2018 and 2023 Censuses.

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The main means of travel to education categories are:

• Study at home

• Drive a car, truck, or van

• Passenger in a car, truck, or van

• Bicycle

• Walk or jog

• School bus

• Public bus

• Train

• Ferry

• Other.

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Main means of travel to education is the usual method a person used to travel the longest distance to their place of study.

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Educational institution address is the physical location of the individual’s place of study. Educational institutions include early childhood education, primary school, secondary school, and tertiary education institutions. For individuals who study at home, their educational institution address is the same as their usual residence address.

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Educational institution address is coded to the most detailed geography possible from the available information. This dataset only includes travel to education information for individuals whose educational institution address is available at SA2 level. The sum of the counts for each region in this dataset may not equal the census usually resident population count who are studying (part time or full time) for that region. Educational institution address – 2023 Census: Information by concept has more information.

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This dataset can be used in conjunction with the following spatial files by joining on the SA2 code values:

• Statistical area 2 2023 (generalised)
• Statistical area 2 2023 (Centroid Inside)

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Download data table using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

​

Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data).

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Educational institution address time series

Educational institution address time series data should be interpreted with care at lower geographic levels, such as statistical area 2 (SA2). Methodological improvements in 2023 Census resulted in greater data accuracy, including a greater proportion of people being counted at lower geographic areas compared to the 2018 Census. Educational institution address – 2023 Census: Information by concept has more information.

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Rows excluded from dataset

Rows show SA2 of usual residence by SA2 of educational institution address. Rows with a total population count of less than six have been removed to reduce the size of the dataset, given only a small proportion of SA2-SA2 combinations have commuter flows.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Main means of travel to education quality rating

Main means of travel to education is rated as moderate quality.

Main means of travel to education – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Educational institution address quality rating

Educational institution address is rated as moderate quality.

Educational institution address – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

​

Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for ‘Total stated’ where this applies.

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Symbol

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

Comprehensive dataset of 4 Faculty of sciences in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

New Zealand Government Budget: Appropriations: Output Expenses: Education Review Office data was reported at 4,285.000 NZD th in 2017. This records a decrease from the previous number of 4,509.000 NZD th for 2016. New Zealand Government Budget: Appropriations: Output Expenses: Education Review Office data is updated yearly, averaging 26,828.500 NZD th from Jun 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 29,568.000 NZD th in 2009 and a record low of 3,915.000 NZD th in 2015. New Zealand Government Budget: Appropriations: Output Expenses: Education Review Office data remains active status in CEIC and is reported by New Zealand Treasury. The data is categorized under Global Database’s New Zealand – Table NZ.F010: Government Budget: Appropriations.

Comprehensive dataset of 3 Faculty of media and information sciences in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1 Municipal health departments in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

New Zealand Government Budget: Appropriations: Education Review Office data was reported at 30,449.000 NZD th in 2017. This records a decrease from the previous number of 30,990.000 NZD th for 2016. New Zealand Government Budget: Appropriations: Education Review Office data is updated yearly, averaging 30,587.500 NZD th from Jun 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 31,630.000 NZD th in 2009 and a record low of 29,786.000 NZD th in 2013. New Zealand Government Budget: Appropriations: Education Review Office data remains active status in CEIC and is reported by New Zealand Treasury. The data is categorized under Global Database’s New Zealand – Table NZ.F010: Government Budget: Appropriations.

New Zealand Government Budget: Appropriations: Capital Expenditure: Education Review Office data was reported at 1,100.000 NZD th in 2018. This records a decrease from the previous number of 1,879.000 NZD th for 2017. New Zealand Government Budget: Appropriations: Capital Expenditure: Education Review Office data is updated yearly, averaging 1,774.000 NZD th from Jun 2008 (Median) to 2018, with 11 observations. The data reached an all-time high of 711,495.000 NZD th in 2011 and a record low of 1,100.000 NZD th in 2018. New Zealand Government Budget: Appropriations: Capital Expenditure: Education Review Office data remains active status in CEIC and is reported by New Zealand Treasury. The data is categorized under Global Database’s New Zealand – Table NZ.F010: Government Budget: Appropriations.

Please Note: As announced by the Minister for Immigration and Border Protection on 25 June 2017, the Department of Immigration and Border Protection (DIBP) retired the paper-based Outgoing Passenger Cards (OPC) from 1 July 2017. The information previously gathered via paper-based outgoing passenger cards is now be collated from existing government data and will continue to be provided to users. Further information can be accessed here: http://www.minister.border.gov.au/peterdutton/Pages/removal-of-the-outgoing-passenger-card-jun17.aspx.

Due to the retirement of the OPC, the Australian Bureau of Statistics (ABS) undertook a review of the OAD data based on a new methodology. Further information on this revised methodology is available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/3401.0Appendix2Jul%202017?opendocument&tabname=Notes&prodno=3401.0&issue=Jul%202017&num=&view=

A sampling methodology has been applied to this dataset. This method means that data will not replicate, exactly, data released by the ABS, but the differences should be negligible.

Due to ‘Return to Source’ limitations, data supplied to ABS from non-DIPB sources are also excluded.

Overseas Arrivals and Departures (OAD) data refers to the arrival and departure of Australian residents or overseas visitors, through Australian airports and sea ports, which have been recorded on incoming or outgoing passenger cards. OAD data describes the number of movements of travellers rather than the number of travellers. That is, multiple movements of individual persons during a given reference period are all counted. OAD data will differ from data derived from other sources, such as Migration Program Outcomes, Settlement Database or Visa Grant information. Travellers granted a visa in one year may not arrive until the following year, or may not travel to Australia at all. Some visas permit multiple entries to Australia, so travellers may enter Australia more than once on a visa. Settler Arrivals includes New Zealand citizens and other non-program settlers not included on the Settlement Database. The Settlement Database includes onshore processed grants not included in Settler Arrivals.

These de-identified statistics are periodically checked for privacy and other compliance requirements. The statistics were temporarily removed in March 2024 in response to a question about privacy within the emerging technological environment. Following a thorough review and risk assessment, the Department of Home Affairs has republished the dataset.

Comprehensive dataset of 14 Justice departments in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Abstract

The first national census of Timor-Leste was conducted from the 11th of July to the 30th of July in 2004 with 4,000 interviewers visiting over 190,000 households across the country. The Census provides Asia's newest nation with its first full population count after the traumatic events of 1999 and base line statistics on housing, employment, fertility and literacy. The census statistical data and indicators, at both national and district levels, will assist the country's administrators and international organisations in planning for sustainable development programs.

In July 2002, a mission comprised of experts from the United Nations Population Division, the Australian Bureau of Statistics, and the Malaysian Department of Statistics was asked to explore the feasibility of conducting a Population and Housing Census in the newly independent Timor-Leste. Although considered as a difficult undertaking, it was determined to be viable.

UNFPA organized the necessary technical and human resource support and provided the major part of the funding needed to carry out the census. Since 2002 two UNFPA Census Projects have been supporting census activities and have expended more than three million dollars. This major financial contribution was supplemented by the assistance of other donors: the United States, which among other things paid for some equipment, the printing of questionnaires and other forms, and also funded technical assistance for data editing; Ireland, which funded the census publicity campaign; New Zealand, which provided funding for technical experts; and Australia, which assisted in the training of data input personnel and in funding several technical assistance missions.

Geographic coverage

National

Analysis unit

• Individual,
• Households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire developed for the pilot census went through a review. A consultant from Statistics New Zealand worked on the questionnaires and talked with government ministries, various UN agencies, NGO's and other interested parties about content and format. Where changes were made, small field tests were carried out to confirm workability and acceptability. By January 2004, the questionnaires were ready to present to the Census Technical Committee and then to government agencies for formal acceptance. During that process, some minor changes were made, but the basic questionnaire was maintained.

Three types of questionnaires were used: one for households, one for institutions (prisons, orphanages, convents, hospitals and boarding schools) and one for hotels. This section refers only to the household questionnaire.

The household questionnaire was prepared in four languages: Tetum, Portuguese, Indonesian and English.

The questionnaire was well designed. The format, wording and arrangement of questions received a great deal of attention. It was short, simple, easy to apply, and included most of the standard census questions and items. The purpose here is not to evaluate the questionnaire in detail, but it is important to mention that the data collected with it has proved to be extremely useful for a number or purposes. The usefulness of the data is a good indicator of the format adequacy and organization of the questionnaire and the relevance of the questions included. It is also important to highlight that, up to now, various data analyses have shown that most of the information is reliable. However, it is also important to recognize there is plenty of space for improvement and the questionnaire for the 2010 Census will be much better. Actually, several analyses of the data obtained with the questionnaire clearly show the need to modify the next census questionnaire and, especially, include additional questions.

Cleaning operations

The first activity was checking and editing the waypoint file. Three main problems were found: duplicate waypoints, waypoints where letters were used instead of numbers, and invalid waypoint numbers. In all cases the errors were manually corrected. Duplicate waypoints were removed, alphanumeric numbers with "o" instead of "0" or "B" instead of "8" were rectified, and waypoints close to invalid waypoints were compared to obtain a clue as to what the likely correct number should be.

After linking waypoints with questionnaire data it was realized that the vast majority of waypoint numbers could be linked to their corresponding dwelling sticker numbers. However, it also became apparent that there were still discrepancies between the two databases: Some questionnaires could not be linked to waypoints and some waypoints could not be linked to questionnaires. These problems were solved with the help of maps, comparisons with nearby waypoints and, in some cases, with new visits to suspect dwellings or entire areas. CSPro, a software package developed by the US Bureau of the Census, was used to capture, process, and edit data.

The data capture team was formed as soon as the interviewing was completed. Staff received training in subjects such as understanding the census process, the design of the census forms, and how to operate the data-entry program. Approximately 38 data-entry operators undertook the work in several shifts. The data was captured by keyboard.

After the data was entered, a process of editing and imputation of data was conducted.

It is important to mention data capture and processing was a weak part of the census operation. Data entry had to be repeated because of the many mistakes and errors done the first time. In addition, after the data was finally entered, it took an unnecessarily long period to process end edit it. Data-capture ended in February 2005 and the edited master file was not ready until December 2005. Even then there were still some inconsistencies, especially in fertility and school enrolment data. Such inconsistencies are minor, but they may reduce the credibility of some results.

The underlying causes of the previous problems were poor use of technical assistance, largely due to lack of management continuity. The NSD is aware of this weakness and the need to address it for the next census.

Please Note: As announced by the Minister for Immigration and Border Protection on 25 June 2017, the Department of Immigration and Border Protection (DIBP) retired the paper-based Outgoing Passenger Cards (OPC) from 1 July 2017. The information previously gathered via paper-based outgoing passenger cards is now be collated from existing government data and will continue to be provided to users. Further information can be accessed here: http://www.minister.border.gov.au/peterdutton/Pages/removal-of-the-outgoing-passenger-card-jun17.aspx. Due to the retirement of the OPC, the Australian Bureau of Statistics (ABS) undertook a review of the OAD data based on a new methodology. Further information on this revised methodology is available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/3401.0Appendix2Jul%202017?opendocument&tabname=Notes&prodno=3401.0&issue=Jul%202017&num=&view= A sampling methodology has been applied to this dataset. This method means that data will not replicate, exactly, data released by the ABS, but the differences should be negligible. Due to ‘Return to Source’ limitations, data supplied to ABS from non-DIPB sources are also excluded. Overseas Arrivals and Departures (OAD) data refers to the arrival and departure of Australian residents or overseas visitors, through Australian airports and sea ports, which have been recorded on incoming or outgoing passenger cards. OAD data describes the number of movements of travellers rather than the number of travellers. That is, multiple movements of individual persons during a given reference period are all counted. OAD data will differ from data derived from other sources, such as Migration Program Outcomes, Settlement Database or Visa Grant information. Travellers granted a visa in one year may not arrive until the following year, or may not travel to Australia at all. Some visas permit multiple entries to Australia, so travellers may enter Australia more than once on a visa. Settler Arrivals includes New Zealand citizens and other non-program settlers not included on the Settlement Database. The Settlement Database includes onshore processed grants not included in Settler Arrivals. These de-identified statistics are periodically checked for privacy and other compliance requirements. The statistics were temporarily removed in March 2024 in response to a question about privacy within the emerging technological environment. Following a thorough review and risk assessment, the Department of Home Affairs has republished the dataset.

Comprehensive dataset of 14 Department of Public Safeties in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Auditor General of Canada invited the Auditor-General of South Africa to lead an international peer review of the Office of the Auditor General of Canada (OAG), an assignment that was proudly accepted. This request builds on a commendable record in the OAG of requesting its peers to conduct external reviews of its practices on a periodic basis. A team consisting of reviewers from the supreme audit institutions (SAIs) of New Zealand, Norway, South Africa, Sweden, and the United States of America was convened to conduct the peer review.

Comprehensive dataset of 14 Correctional services departments in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 57 Police departments in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

In 2018, 100 percent of the adult populations in Australia, Hong Kong, Japan, Taiwan, South Korea, and New Zealand had their credit information covered by a private credit bureau. In comparison, less than seven percent of the adult population in Pakistan had their credit information covered by a private credit bureau in 2020.

Comprehensive dataset of 3 Department of housings in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1 Office of Vital Records in New Zealand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.