In 2021, Muslims around the world spent a total of *** trillion U.S. dollars across the food, pharmaceutical, cosmetics, fashion, travel, and media/recreation sectors. The global Muslim market has the potential to grow to about *** trillion dollars by 2025. The largest market for Muslim consumers is the halal food and beverage sector.

As of 2021, approximately **** percent of the population in Aceh, Indonesia were Muslims. Despite being the largest Muslim-majority country, Indonesia is a multi-faith country by the constitution and officially recognizes *** religions – Islam, Protestantism, Catholicism, Buddhism, Hinduism, and Confucianism.

Over the 12 months to the fouth quarter of 2021, deposits taken by Islamic banks grew at nearly *** percent, while financing grew at nearly ** percent. These figures are in stark contrast to the compound annual growth rate of Islamic banks measured from March 2014 to September 2020, where both financing and deposits experienced declines of **** and **** percent respectively.

The Hajj Dataset 2021-2024: Ministry of Religious Affairs Malang City contains comprehensive data on the Hajj pilgrimage process for 2021 through 2024, gathered explicitly from the Malang City branch of Indonesia's Ministry of Religious Affairs (Kemenag). This dataset captures key information about the Hajj pilgrimage, including payment records, associated costs, and demographic details of the pilgrims, providing valuable insights into the financial aspects and trends over the four years. Key Data Features: Yearly Hajj Costs: Information on the financial breakdown of Hajj costs for each year, covering all components, including transportation, accommodation, and other mandatory fees. Pilgrim Demographics: Data on the number and characteristics of pilgrims from Malang City, including age, gender, and other socioeconomic indicators. Payment Status and History: Records of payments made by the pilgrims detailing the timing, amount, and any outstanding balances. Regulatory Changes: Information on changes in the regulations and policies of the Ministry of Religious Affairs (Kemenag) that may have impacted the cost structure or payment schedule during this period. Inflation and Currency Impact: Data reflecting the impact of national inflation rates or currency fluctuations, particularly the value of the Indonesian Rupiah (IDR) relative to the Saudi Riyal (SAR), on the overall pilgrimage cost. Hajj Quota and Registrations: The number of Hajj applicants from Malang City and the annual quota allocated to the region, including details on the selection process and waiting periods. Potential Use Cases: Cost Prediction: Analyze cost trends and predict future financial needs for the Hajj pilgrimage. Policy Analysis: Assess the impact of government policies on the affordability and accessibility of Hajj for pilgrims. Economic Analysis: Understand how national economic factors (inflation and and exchange rates) affect pilgrimage costs. Social Research: Study demographic patterns and regional participation in Hajj from Malang City. This dataset provides an essential resource for anyone interested in the economic, social, and policy dimensions of the Hajj pilgrimage in Indonesia, particularly in the context of Malang City's unique data.

In 2021, 57 percent of the Muslim population aged 15 and over held the marital status of married. On the other hand, 37 percent of the community members were registered as single. Divorced and widowed people each accounted for three percent of the population.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Iran, Islamic Rep. is 1005.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Census 2021 data on religion by economic activity status, by sex, by age, and religion by occupation, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged between 16 to 64 years old only. This is to focus on religious affiliation differences among the working age. Population counts in these tables may be different from other publications which use different age breakdowns.

Quality notes can be found here

Quality information about Labour Market can be found here

The Standard Occupation Classification 2020 code used can be found here

Religion

The 8 ‘tickbox’ religious groups are as follows:

• Buddhist
• Christian
• Hindu
• Jewish
• Muslim
• No religion
• Sikh
• Other religion

Export: Services: Organization of Islamic Cooperation data was reported at 9.781 USD bn in 2022. This records an increase from the previous number of 7.714 USD bn for 2021. Export: Services: Organization of Islamic Cooperation data is updated yearly, averaging 7.583 USD bn from Dec 2018 (Median) to 2022, with 5 observations. The data reached an all-time high of 9.781 USD bn in 2022 and a record low of 5.292 USD bn in 2020. Export: Services: Organization of Islamic Cooperation data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.JA074: Trade Statistics: Services: by Country Group.

Population Growth for the Islamic Republic of Iran was 1.20408 % Chg. at Annual Rate in January of 2023, according to the United States Federal Reserve. Historically, Population Growth for the Islamic Republic of Iran reached a record high of 4.13505 in January of 1983 and a record low of 0.83103 in January of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Growth for the Islamic Republic of Iran - last updated from the United States Federal Reserve on July of 2025.

Turkey Import: Services: Organization of Islamic Cooperation data was reported at 2.575 USD bn in 2022. This records an increase from the previous number of 1.883 USD bn for 2021. Turkey Import: Services: Organization of Islamic Cooperation data is updated yearly, averaging 1.991 USD bn from Dec 2018 (Median) to 2022, with 5 observations. The data reached an all-time high of 2.575 USD bn in 2022 and a record low of 1.334 USD bn in 2020. Turkey Import: Services: Organization of Islamic Cooperation data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.JA074: Trade Statistics: Services: by Country Group.

Investment deposits of the Foundation for the development of orphans' funds in Islamic banks Data and Resources Copy of ودائع لدى البنوك الاسلاميةXLS Copy of ودائع لدى البنوك الاسلامية Explore Preview Download ودائع لدى البنوك الاسلامية2021XLS ودائع لدى البنوك الاسلامية2021 Explore Preview Download

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly

Sampling procedure

Sample size:

This dataset shows the Non-Muslim marriages by state (place of residence), Malaysia, 2016-2021 Source: Department of Statistics, Malaysia No. of Views : 89

Saudi Arabia and Malaysia accounted for almost two thirds of the total assets held by Islamic funds in 2021. Jersey was the next largest, with 13.4 percent, while no other single country accounted for more that five percent. However, this list refers to where the funds are domiciled, meaning that the investors who own shares in the fund may not necessarily live in the same country.

This repository contains historical data collected in the digital humanities project Dhimmis & Muslims – Analysing Multireligious Spaces in the Medieval Muslim World. The project was funded by the VolkswagenFoundation within the scope of the Mixed Methods initiative. The project was a collaboration between the Institute for Medieval History II of the Goethe University in Frankfurt/Main, Germany, and the Institute for Visualization and Interactive Systems at the University of Stuttgart, and took place there from 2018 to 2021. The objective of this joint project was to develop a novel visualization approach in order to gain new insights on the multi-religious landscapes of the Middle East under Muslim rule during the Middle Ages (7th to 14th century). In particular, information on multi-religious communities were researched and made available in a database accessible through interactive visualization as well as through a pilot web-based geo-temporal multi-view system to analyze and compare information from multiple sources. The code for this visualization system is publicly available on GitHub under the MIT license. The data in this repository is a curated database dump containing data collected from a predetermined set of primary historical sources and literature. The core objective of the data entry was to record historical evidence for religious groups in cities of the Medieval Middle East. In the project, data was collected in a relational PostgreSQL database, the structure of which can be reconstructed from the file schema.sql. An entire database dump including both the database schema and the table contents is located in database.sql. The PDF file database-structure.pdf describes the relationship between tables in a graphical schematic. In the database.json file, the contents of the individual tables are stored in JSON format. At the top level, the JSON file is an object. Each table is stored as a key-value pair, where the key is the database name, and the value is an array of table records. Each table record is itself an object of key-value pairs, where the keys are the table columns, and the values are the corresponding values in the record. The dataset is centered around the evidence, which represents one piece of historical evidence as extracted from one or more sources. An evidence must contain a reference to a place and a religion, and may reference a person and one or more time spans. Instances are used to connect evidences to places, persons, and religions; and additional metadata are stored individually in the instances. Time instances are connected to the evidence via a time group to allow for more than one time span per evidence. An evidence is connected via one or more source instances to one or more sources. Evidences can also be tagged with one or more tags via the tag_evidence table. Places and persons have a type, which are defined in the place type and person type tables. Alternative names for places are stored in the name_var table with a reference to the respective language. For places and persons, references to URIs in other data collections (such as Syriaca.org or the Digital Atlas of the Roman Empire) are also stored, in the external_place_uri and external_person_uri tables. Rules for how to construct the URIs from the fragments stored in the last-mentioned tables are controlled via the uri_namespace and external_database tables. Part of the project was to extract historical evidence from digitized texts, via annotations. Annotations are placed in a document, which is a digital version of a source. An annotation can be one of the four instance types, thereby referencing a place, person, religion, or time group. A reference to the annotation is stored in the instance, and evidences are constructed from annotations by connecting the respective instances in an evidence tuple.

Census: Population: by Religion: Muslim: Uttarakhand data was reported at 1,406,825.000 Person in 03-01-2011. This records an increase from the previous number of 1,012,141.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand data is updated decadal, averaging 1,209,483.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 1,406,825.000 Person in 03-01-2011 and a record low of 1,012,141.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE003: Census: Population: by Religion: Muslim.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

Census 2021 data on religion by general health, by sex, by age; religion by disability, by sex, by age; and, religion by unpaid care, by sex, by age; England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

The population base for unpaid care is usual residents aged 5 years and above. We have used 5-year age bands for the majority of analysis; however, age groups "5 to 17" and "18 to 24" have been used to allow commentary on young carers and young working age carers.

Quality notes can be found here

Religion

The 8 ‘tickbox’ religious groups are as follows:

• Buddhist
• Christian
• Hindu
• Jewish
• Muslim
• No religion
• Sikh
• Other religion

General health

A person's assessment of the general state of their health from very good to very bad. This assessment is not based on a person's health over any specified period of time.

Disability

The definition of disability used in the 2021 Census is aligned with the definition of disability under the Equality Act (2010). A person is considered disabled if they self-report having a physical or mental health condition or illness that has lasted or is expected to last 12 months or more, and that this reduces their ability to carry out day-to-day activities.

Unpaid care

An unpaid carer may look after, give help or support to anyone who has long-term physical or mental ill-health conditions, illness or problems related to old age. This does not include any activities as part of paid employment. This help can be within or outside of the carer's household.

In 2021, the largest market for Muslim-friendly travel market was Turkey, valued at almost 5.7 billion U.S. dollars. In comparison, Malaysia had a market value for the Muslim travel segment of 2.4 billion U.S. dollars.