Sample data for exercises in Further Adventures in Data Cleaning.

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Data Quality Management Service Market Outlook

The global data quality management service market size was valued at approximately USD 1.8 billion in 2023 and is projected to reach USD 5.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 14.1% during the forecast period. The primary growth factor driving this market is the increasing volume of data being generated across various industries, necessitating robust data quality management solutions to maintain data accuracy, reliability, and relevance.

One of the key growth drivers for the data quality management service market is the exponential increase in data generation due to the proliferation of digital technologies such as IoT, big data analytics, and AI. Organizations are increasingly recognizing the importance of maintaining high data quality to derive actionable insights and make informed business decisions. Poor data quality can lead to significant financial losses, inefficiencies, and missed opportunities, thereby driving the demand for comprehensive data quality management services.

Another significant growth factor is the rising regulatory and compliance requirements across various industry verticals such as BFSI, healthcare, and government. Regulations like the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA) necessitate organizations to maintain accurate and high-quality data. Non-compliance with these regulations can result in severe penalties and damage to the organization’s reputation, thus propelling the adoption of data quality management solutions.

Additionally, the increasing adoption of cloud-based solutions is further fueling the growth of the data quality management service market. Cloud-based data quality management solutions offer scalability, flexibility, and cost-effectiveness, making them an attractive option for organizations of all sizes. The availability of advanced data quality management tools that integrate seamlessly with existing IT infrastructure and cloud platforms is encouraging enterprises to invest in these services to enhance their data management capabilities.

From a regional perspective, North America is expected to hold the largest share of the data quality management service market, driven by the early adoption of advanced technologies and the presence of key market players. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, owing to the rapid digital transformation, increasing investments in IT infrastructure, and growing awareness about the importance of data quality management in enhancing business operations and decision-making processes.

Component Analysis

The data quality management service market is segmented by component into software and services. The software segment encompasses various data quality tools and platforms that help organizations assess, improve, and maintain the quality of their data. These tools include data profiling, data cleansing, data enrichment, and data monitoring solutions. The increasing complexity of data environments and the need for real-time data quality monitoring are driving the demand for sophisticated data quality software solutions.

Services, on the other hand, include consulting, implementation, and support services provided by data quality management service vendors. Consulting services assist organizations in identifying data quality issues, developing data governance frameworks, and implementing best practices for data quality management. Implementation services involve the deployment and integration of data quality tools with existing IT systems, while support services provide ongoing maintenance and troubleshooting assistance. The growing need for expert guidance and support in managing data quality is contributing to the growth of the services segment.

The software segment is expected to dominate the market due to the continuous advancements in data quality management tools and the increasing adoption of AI and machine learning technologies for automated data quality processes. Organizations are increasingly investing in advanced data quality software to streamline their data management operations, reduce manual intervention, and ensure data accuracy and consistency across various data sources.

Moreover, the services segment is anticipated to witness significant growth during the forecast period, driven by the increasing demand for professional services that can help organizations address complex dat

The scientific community has entered an era of big data. However, with big data comes big responsibilities, and best practices for how data are contributed to databases have not kept pace with the collection, aggregation, and analysis of big data. Here, we rigorously assess the quantity of data for specific leaf area (SLA) available within the largest and most frequently used global plant trait database, the TRY Plant Trait Database, exploring how much of the data were applicable (i.e., original, representative, logical, and comparable) and traceable (i.e., published, cited, and consistent). Over three-quarters of the SLA data in TRY either lacked applicability or traceability, leaving only 22.9% of the original data usable compared to the 64.9% typically deemed usable by standard data cleaning protocols. The remaining usable data differed markedly from the original for many species, which led to altered interpretation of ecological analyses. Though the data we consider here make up onl..., SLA data was downlaoded from TRY (traits 3115, 3116, and 3117) for all conifer (Araucariaceae, Cupressaceae, Pinaceae, Podocarpaceae, Sciadopityaceae, and Taxaceae), Plantago, Poa, and Quercus species. The data has not been processed in any way, but additional columns have been added to the datset that provide the viewer with information about where each data point came from, how it was cited, how it was measured, whether it was uploaded correctly, whether it had already been uploaded to TRY, and whether it was uploaded by the individual who collected the data., , There are two additional documents associated with this publication. One is a word document that includes a description of each of the 120 datasets that contained SLA data for the four plant groups within the study (conifers, Plantago, Poa, and Quercus). The second is an excel document that contains the SLA data that was downloaded from TRY and all associated metadata.

Missing data codes: NA and N/A

The use of in vitro new approach methodologies (NAMs) to assess respiratory irritation depends on several factors, including the specifics of exposure methods and cell/tissue-based test systems. This topic was examined in the context of human health risk assessment for cleaning products at a 1-day public workshop held on 2 March 2023, organized by the American Cleaning Institute® (ACI). The goals of this workshop were to (1) review in vitro NAMs for evaluation of respiratory irritation, (2) examine different perspectives on current challenges and suggested solutions, and (3) publish a manuscript of the proceedings. Targeted sessions focused on exposure methods, in vitro cell/tissue test systems, and application to human health risk assessment. The importance of characterization of assays and development of reporting standards was noted throughout the workshop. The exposure methods session emphasized that the appropriate exposure system design depends on the purpose of the assessment. This is particularly important given the many dosimetry and technical considerations affecting relevance and translation of results to human exposure scenarios. Discussion in the in vitro cell/tissue test systems session focused on the wide variety of cell systems with varying suitability for evaluating key mechanistic steps, such as molecular initiating events (MIEs) and key events (KEs) likely present in any putative respiratory irritation adverse outcome pathway (AOP). This suggests the opportunity to further develop guidance around in vitro cell/tissue test system endpoint selection, assay design, characterization and validation, and analytics that provide information about a given assay’s utility. The session on applications for human health protection emphasized using mechanistic understanding to inform the choice of test systems and integration of NAMs-derived data with other data sources (e.g., physicochemical properties, exposure information, and existing in vivo data) as the basis for in vitro to in vivo extrapolation. In addition, this group noted a need to develop procedures to align NAMs-based points of departure (PODs) and uncertainty factor selection with current human health risk assessment methods, together with consideration of elements unique to in vitro data. Current approaches are described and priorities for future characterization of in vitro NAMs to assess respiratory irritation are noted.

The Wheel Drive Swimming Pool Cleaning Robots market is witnessing significant growth as more homeowners and pool facilities seek efficient and automated solutions for maintaining pristine swimming environments. These innovative devices are engineered to navigate the pool floor and walls with precision, utilizing ad

The Gun Cleaning Kits market is an essential segment of the broader firearms industry, catering to the maintenance and longevity of firearms through specialized cleaning solutions. These kits typically include a variety of tools such as brushes, patches, solvents, and oils, designed to remove fouling, corrosion, and

Removal of leaf-litter may help municipalities reduce phosphorus loads. Catch-basin cleaning and street cleaning are two commonly used Best Management Practices that could be modified to remove leaves and qualify for additional load-reduction credits. This Data Release contains four tab-delimited .txt files containing additional information about the study area, characteristics of municipal street solids, and load-reduction estimates from increased catch basin and street cleaning practices that are not available in the associated report. This Data Release also contains a compressed file, "EngBrk_ModelArchive.7z", which archives the model developed and used for the project. The four .txt table files are: (1) "VT_LU_data.txt", which includes the area, in acres and percent, for each land-use type within the nine participating municipalities and within the Englesby Brook basin (based on the National Oceanic and Atmospheric Administration's (NOAA) 2006 C-CAP Regional Land Cover); (2) "CB_sample_characteristics.txt", which describes the physical characteristics of samples collected from piles of catch-basin solids for nine municipalities in this study (September to November 2017 and April to November 2018); (3) "SC_sample_characteristics.txt", which describes the physical characteristics of samples collected from piles of street-cleaning solids for nine municipalities in this study (September to November 2017 and April to November 2018); and (4) "Estimated P-load reductions.txt", which contains estimated phosphorus load-reduction credits by using individual Soil Water Assessment Tool (SWAT) drainage areas for street cleaning and street cleaning with leaf management practices for the seven participating Municipal Separate Storm Sewer Systems (MS4s) municipalities in northwestern Vermont. The cities of Barre and Montpelier currently do not have to meet MS4 permit requirements. Information from the NOAA's 2006 C-CAP Regional Land Cover (https://data.noaa.gov/dataset/dataset/noaas-coastal-change-analysis-program-c-cap-2006-regional-land-cover-data-coastal-united-state1) and the Vermont Center for Geographic Information (https://vcgi.vermont.gov/) were used to characterize land use within each of the nine municipalities in the central and northwestern Vermont, study area, and the partially urbanized Englesby Brook basin located in Burlington and South Burlington, Vermont, that drains into Lake Champlain. The compressed file "EngBrk_ModelArchive.7z" represents the model archive that contains 31 files associated with the Englesby Brook model using the Source Loading and Management Model for Windows (WinSLAMM) version 10.4.0.

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Data Visualization Tools Market Size 2025-2029

The data visualization tools market size is forecast to increase by USD 7.95 billion at a CAGR of 11.2% between 2024 and 2029.

The market is experiencing significant growth due to the increasing demand for business intelligence and AI-powered insights. Companies are recognizing the value of transforming complex data into easily digestible visual representations to inform strategic decision-making. However, this market faces challenges as data complexity and massive data volumes continue to escalate. Organizations must invest in advanced data visualization tools to effectively manage and analyze their data to gain a competitive edge. The ability to automate data visualization processes and integrate AI capabilities will be crucial for companies to overcome the challenges posed by data complexity and volume. By doing so, they can streamline their business operations, enhance data-driven insights, and ultimately drive growth in their respective industries.

What will be the Size of the Data Visualization Tools Market during the forecast period?

Request Free SampleIn today's data-driven business landscape, the market continues to evolve, integrating advanced capabilities to support various sectors in making informed decisions. Data storytelling and preparation are crucial elements, enabling organizations to effectively communicate complex data insights. Real-time data visualization ensures agility, while data security safeguards sensitive information. Data dashboards facilitate data exploration and discovery, offering data-driven finance, strategy, and customer experience. Big data visualization tackles complex datasets, enabling data-driven decision making and innovation. Data blending and filtering streamline data integration and analysis. Data visualization software supports data transformation, cleaning, and aggregation, enhancing data-driven operations and healthcare. On-premises and cloud-based solutions cater to diverse business needs. Data governance, ethics, and literacy are integral components, ensuring data-driven product development, government, and education adhere to best practices. Natural language processing, machine learning, and visual analytics further enrich data-driven insights, enabling interactive charts and data reporting. Data connectivity and data-driven sales fuel business intelligence and marketing, while data discovery and data wrangling simplify data exploration and preparation. The market's continuous dynamism underscores the importance of data culture, data-driven innovation, and data-driven HR, as organizations strive to leverage data to gain a competitive edge.

How is this Data Visualization Tools Industry segmented?

The data visualization tools 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. DeploymentOn-premisesCloudCustomer TypeLarge enterprisesSMEsComponentSoftwareServicesApplicationHuman resourcesFinanceOthersEnd-userBFSIIT and telecommunicationHealthcareRetailOthersGeographyNorth AmericaUSMexicoEuropeFranceGermanyUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.The market has experienced notable expansion as businesses across diverse sectors acknowledge the significance of data analysis and representation to uncover valuable insights and inform strategic decisions. Data visualization plays a pivotal role in this domain. On-premises deployment, which involves implementing data visualization tools within an organization's physical infrastructure or dedicated data centers, is a popular choice. This approach offers organizations greater control over their data, ensuring data security, privacy, and adherence to data governance policies. It caters to industries dealing with sensitive data, subject to regulatory requirements, or having stringent security protocols that prohibit cloud-based solutions. Data storytelling, data preparation, data-driven product development, data-driven government, real-time data visualization, data security, data dashboards, data-driven finance, data-driven strategy, big data visualization, data-driven decision making, data blending, data filtering, data visualization software, data exploration, data-driven insights, data-driven customer experience, data mapping, data culture, data cleaning, data-driven operations, data aggregation, data transformation, data-driven healthcare, on-premises data visualization, data governance, data ethics, data discovery, natural language processing, data reporting, data visualization platforms, data-driven innovation, data wrangling, data-driven s

Abstract

The 2016 Integrated Household Panel Survey (IHPS) was launched in April 2016 as part of the Malawi Fourth Integrated Household Survey fieldwork operation. The IHPS 2016 targeted 1,989 households that were interviewed in the IHPS 2013 and that could be traced back to half of the 204 enumeration areas that were originally sampled as part of the Third Integrated Household Survey (IHS3) 2010/11. The 2019 IHPS was launched in April 2019 as part of the Malawi Fifth Integrated Household Survey fieldwork operations targeting the 2,508 households that were interviewed in 2016. The panel sample expanded each wave through the tracking of split-off individuals and the new households that they formed. Available as part of this project is the IHPS 2019 data, the IHPS 2016 data as well as the rereleased IHPS 2010 & 2013 data including only the subsample of 102 EAs with updated panel weights. Additionally, the IHPS 2016 was the first survey that received complementary financial and technical support from the Living Standards Measurement Study – Plus (LSMS+) initiative, which has been established with grants from the Umbrella Facility for Gender Equality Trust Fund, the World Bank Trust Fund for Statistical Capacity Building, and the International Fund for Agricultural Development, and is implemented by the World Bank Living Standards Measurement Study (LSMS) team, in collaboration with the World Bank Gender Group and partner national statistical offices. The LSMS+ aims to improve the availability and quality of individual-disaggregated household survey data, and is, at start, a direct response to the World Bank IDA18 commitment to support 6 IDA countries in collecting intra-household, sex-disaggregated household survey data on 1) ownership of and rights to selected physical and financial assets, 2) work and employment, and 3) entrepreneurship – following international best practices in questionnaire design and minimizing the use of proxy respondents while collecting personal information. This dataset is included here.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Children under 5 years
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop

Universe

The IHPS 2016 and 2019 attempted to track all IHPS 2013 households stemming from 102 of the original 204 baseline panel enumeration areas as well as individuals that moved away from the 2013 dwellings between 2013 and 2016 as long as they were neither servants nor guests at the time of the IHPS 2013; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sub-sample of IHS3 2010 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS 2013) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban. The IHPS 2013 main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.

Given budget and resource constraints, for the IHPS 2016 the number of sample EAs in the panel was reduced to 102 out of the 204 EAs. As a result, the domains of analysis are limited to the national, urban and rural areas. Although the results of the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS by region, urban and rural strata was maintained. The IHPS 2019 tracked all individuals 12 years or older from the 2016 households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Data Entry Platform To ensure data quality and timely availability of data, the IHPS 2019 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHPS 2019, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer that the NSO provided. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

Data Management The IHPS 2019 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHPS 2019 Interviews were mainly collected in “sample” mode (assignments generated from headquarters) and a few in “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample. This hybrid approach was necessary to aid the tracking operations whereby an enumerator could quickly create a tracking assignment considering that they were mostly working in areas with poor network connection and hence could not quickly receive tracking cases from Headquarters.

The range and consistency checks built into the application was informed by the LSMS-ISA experience with the IHS3 2010/11, IHPS 2013 and IHPS 2016. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (the NSO management) assigned work to the supervisors based on their regions of coverage. The supervisors then made assignments to the enumerators linked to their supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHPS 2019 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to Stata for other consistency checks, data cleaning, and analysis.

Data Cleaning The data cleaning process was done in several stages over the course of fieldwork and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field-based field teams utilizing error messages generated by the Survey Solutions application when a response did not fit the rules for a particular question. For questions that flagged an error, the enumerators were expected to record a comment within the questionnaire to explain to their supervisor the reason for the error and confirming that they double checked the response with the respondent. The supervisors were expected to sync the enumerator tablets as frequently as possible to avoid having many questionnaires on the tablet, and to enable daily checks of questionnaires. Some supervisors preferred to review completed interviews on the tablets so they would review prior to syncing but still record the notes in the supervisor account and reject questionnaires accordingly. The second stage of data cleaning was also done in the field, and this resulted from the additional error reports generated in Stata, which were in turn sent to the field teams via email or DropBox. The field supervisors collected reports for their assignments and in coordination with the enumerators reviewed, investigated, and collected errors. Due to the quick turn-around in error reporting, it was possible to conduct call-backs while the team was still operating in the EA when required. Corrections to the data were entered in the rejected questionnaires and sent back to headquarters.

The data cleaning process was done in several stages over the course of the fieldwork and through preliminary analyses. The first stage was during the interview itself. Because CAPI software was used, as enumerators asked the questions and recorded information, error messages were provided immediately when the information recorded did not match previously defined rules for that variable. For example, if the education level for a 12 year old respondent was given as post graduate. The second stage occurred during the review of the questionnaire by the Field Supervisor. The Survey Solutions software allows errors to remain in the data if the enumerator does not make a correction. The enumerator can write a comment to explain why the data appears to be incorrect. For example, if the previously mentioned 12 year old was, in fact, a genius who had completed graduate studies. The next stage occurred when the data were transferred to headquarters where the NSO staff would again review the data for errors and verify the comments from the

Abstract

The 2003 Agriculture Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmer organisations, etc. As a result the dataset is both more numerous in its sample and detailed in its scope compared to previous censuses and surveys. To date this is the most detailed Agricultural Census carried out in Africa.

The census was carried out in order to: · Identify structural changes if any, in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in rural infrastructure and in the level of agriculture household living conditions; · Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stake holders. · Establish baseline data for the measurement of the impact of high level objectives of the Agriculture Sector Development Programme (ASDP), National Strategy for Growth and Reduction of Poverty (NSGRP) and other rural development programs and projects. · Obtain benchmark data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing, service delivery, etc.

Geographic coverage

Tanzania Mainland and Zanzibar

Analysis unit

• Households
• Individuals

Universe

Large scale, small scale and community farms.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The Mainland sample consisted of 3,221 villages. These villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the 2002 Population and Housing Census. The total Mainland sample was 48,315 agricultural households. In Zanzibar a total of 317 enumeration areas (EAs) were selected and 4,755 agriculture households were covered. Nationwide, all regions and districts were sampled with the exception of three urban districts (two from Mainland and one from Zanzibar).

In both Mainland and Zanzibar, a stratified two stage sample was used. The number of villages/EAs selected for the first stage was based on a probability proportional to the number of villages in each district. In the second stage, 15 households were selected from a list of farming households in each selected Village/EA, using systematic random sampling, with the village chairpersons assisting to locate the selected households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The census covered agriculture in detail as well as many other aspects of rural development and was conducted using three different questionnaires: • Small scale questionnaire • Community level questionnaire • Large scale farm questionnaire

The small scale farm questionnaire was the main census instrument and it includes questions related to crop and livestock production and practices; population demographics; access to services, resources and infrastructure; and issues on poverty, gender and subsistence versus profit making production unit.

The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices.

The large scale farm questionnaire was administered to large farms either privately or corporately managed.

Questionnaire Design The questionnaires were designed following user meetings to ensure that the questions asked were in line with users data needs. Several features were incorporated into the design of the questionnaires to increase the accuracy of the data: • Where feasible all variables were extensively coded to reduce post enumeration coding error. • The definitions for each section were printed on the opposite page so that the enumerator could easily refer to the instructions whilst interviewing the farmer. • The responses to all questions were placed in boxes printed on the questionnaire, with one box per character. This feature made it possible to use scanning and Intelligent Character Recognition (ICR) technologies for data entry. • Skip patterns were used to reduce unnecessary and incorrect coding of sections which do not apply to the respondent. • Each section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data type coding for the programming of CSPro, SPSS and the dissemination applications.

Cleaning operations

Data processing consisted of the following processes: · Data entry · Data structure formatting · Batch validation · Tabulation

Data Entry Scanning and ICR data capture technology for the small holder questionnaire were used on the Mainland. This not only increased the speed of data entry, it also increased the accuracy due to the reduction of keystroke errors. Interactive validation routines were incorporated into the ICR software to track errors during the verification process. The scanning operation was so successful that it is highly recommended for adoption in future censuses/surveys. In Zanzibar all data was entered manually using CSPro.

Prior to scanning, all questionnaires underwent a manual cleaning exercise. This involved checking that the questionnaire had a full set of pages, correct identification and good handwriting. A score was given to each questionnaire based on the legibility and the completeness of enumeration. This score will be used to assess the quality of enumeration and supervision in order to select the best field staff for future censuses/surveys.

CSPro was used for data entry of all Large Scale Farm and community based questionnaires due to the relatively small number of questionnaires. It was also used to enter data from the 2,880 small holder questionnaires that were rejected by the ICR extraction application.

Data Structure Formatting A program was developed in visual basic to automatically alter the structure of the output from the scanning/extraction process in order to harmonise it with the manually entered data. The program automatically checked and changed the number of digits for each variable, the record type code, the number of questionnaires in the village, the consistency of the Village ID Code and saved the data of one village in a file named after the village code.

Batch Validation A batch validation program was developed in order to identify inconsistencies within a questionnaire. This is in addition to the interactive validation during the ICR extraction process. The procedures varied from simple range checking within each variable to the more complex checking between variables. It took six months to screen, edit and validate the data from the smallholder questionnaires. After the long process of data cleaning, tabulations were prepared based on a pre-designed tabulation plan.

Tabulations Statistical Package for Social Sciences (SPSS) was used to produce the Census tabulations and Microsoft Excel was used to organize the tables and compute additional indicators. Excel was also used to produce charts while ArcView and Freehand were used for the maps.

Analysis and Report Preparation The analysis in this report focuses on regional comparisons, time series and national production estimates. Microsoft Excel was used to produce charts; ArcView and Freehand were used for maps, whereas Microsoft Word was used to compile the report.

Data Quality A great deal of emphasis was placed on data quality throughout the whole exercise from planning, questionnaire design, training, supervision, data entry, validation and cleaning/editing. As a result of this, it is believed that the census is highly accurate and representative of what was experienced at field level during the Census year. With very few exceptions, the variables in the questionnaire are within the norms for Tanzania and they follow expected time series trends when compared to historical data. Standard Errors and Coefficients of Variation for the main variables are presented in the Technical Report (Volume I).

Sampling error estimates

The Sampling Error found on page (21) up to page (22) in the Technical Report for Agriculture Sample Census Survey 2002-2003

The datasets presented here were partially used in “Formulation and MIP-heuristics for the lot sizing and scheduling problem with temporal cleanings” (Toscano, A., Ferreira, D. , Morabito, R. , Computers & Chemical Engineering) [1], in “A decomposition heuristic to solve the two-stage lot sizing and scheduling problem with temporal cleaning” (Toscano, A., Ferreira, D. , Morabito, R. , Flexible Services and Manufacturing Journal) [2], and in “A heuristic approach to optimize the production scheduling of fruit-based beverages” (Toscano et al., Gestão & Produção, 2020) [3]. In fruit-based production processes, there are two production stages: preparation tanks and production lines. This production process has some process-specific characteristics, such as temporal cleanings and synchrony between the two production stages, which make optimized production planning and scheduling even more difficult. In this sense, some papers in the literature have proposed different methods to solve this problem. To the best of our knowledge, there are no standard datasets used by researchers in the literature in order to verify the accuracy and performance of proposed methods or to be a benchmark for other researchers considering this problem. The authors have been using small data sets that do not satisfactorily represent different scenarios of production. Since the demand in the beverage sector is seasonal, a wide range of scenarios enables us to evaluate the effectiveness of the proposed methods in the scientific literature in solving real scenarios of the problem. The datasets presented here include data based on real data collected from five beverage companies. We presented four datasets that are specifically constructed assuming a scenario of restricted capacity and balanced costs. These dataset is supplementary data for the submitted paper to Data in Brief [4]. [1] Toscano, A., Ferreira, D., Morabito, R., Formulation and MIP-heuristics for the lot sizing and scheduling problem with temporal cleanings, Computers & Chemical Engineering. 142 (2020) 107038. Doi: 10.1016/j.compchemeng.2020.107038. [2] Toscano, A., Ferreira, D., Morabito, R., A decomposition heuristic to solve the two-stage lot sizing and scheduling problem with temporal cleaning, Flexible Services and Manufacturing Journal. 31 (2019) 142-173. Doi: 10.1007/s10696-017-9303-9. [3] Toscano, A., Ferreira, D., Morabito, R., Trassi, M. V. C., A heuristic approach to optimize the production scheduling of fruit-based beverages. Gestão & Produção, 27(4), e4869, 2020. https://doi.org/10.1590/0104-530X4869-20. [4] Piñeros, J., Toscano, A., Ferreira, D., Morabito, R., Datasets for lot sizing and scheduling problems in the fruit-based beverage production process. Data in Brief (2021).

In order to effectively fight against aquatic invasive species, the Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks has formulated a series of best practices. Among these good practices, cleaning watercraft greatly reduces the risks of dispersal of aquatic invasive species, whether animals or plants. In recent years, several municipalities in Quebec have installed cleaning stations (permanent or mobile), near water bodies, in order to protect them from the arrival of new invasive species or to reduce the risks of dispersion. The MELCCFP participated in this effort by funding several cleaning stations through its funding program. In order to facilitate the planning of nautical activities for citizens, it is important to make the location of these cleaning stations available. Thus, this dataset lists the location, address and name of known cleaning stations in Quebec. WARNINGS: * The identification of these stations was carried out in collaboration with the Reunification of organizations of watersheds of Quebec and the Laurentides Regional Environment Council, as part of projects funded by Fisheries and Oceans Canada, as well as the organizations managing the stations. There may be a time lag between the position listed in the data set and the actual location of the station. If you notice such a discrepancy, please inform the data set managers so that the necessary corrections can be made. * The “mobile” cleaning stations were positioned at their most frequent locations during the year. Depending on the season and current events in a location, mobile stations may not be parked at the location listed. ** Update ** * If you believe that information is incorrect for one of the stations, please send dpefa@environnement.gouv.qc.ca the information that needs to be changed to with the information that needs to be changed, including the unique identifier of the station (Station_Identifier field) in question.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Removal of leaf-litter may help municipalities reduce phosphorus loads. Catch-basin cleaning and street cleaning are two commonly used Best Management Practices that could be modified to remove leaves and qualify for additional load-reduction credits. This Data Release contains four tab-delimited .txt files containing additional information about the study area, characteristics of municipal street solids, and load-reduction estimates from increased catch basin and street cleaning practices that are not available in the associated report. This Data Release also contains a compressed file, "EngBrk_ModelArchive.7z", which archives the model developed and used for the project. The four .txt table files are: (1) "VT_LU_data.txt", which includes the area, in acres and percent, for each land-use type within the nine participating municipalities and within the Englesby Brook basin (based on the National Oceanic and Atmospheric Administration's (NOAA) 2006 C-CAP Regional Land Cover); (2) "CB_sample_characteristics.txt", which describes the physical characteristics of samples collected from piles of catch-basin solids for nine municipalities in this study (September to November 2017 and April to November 2018); (3) "SC_sample_characteristics.txt", which describes the physical characteristics of samples collected from piles of street-cleaning solids for nine municipalities in this study (September to November 2017 and April to November 2018); and (4) "Estimated P-load reductions.txt", which contains estimated phosphorus load-reduction credits by using individual Soil Water Assessment Tool (SWAT) drainage areas for street cleaning and street cleaning with leaf management practices for the seven participating Municipal Separate Storm Sewer Systems (MS4s) municipalities in northwestern Vermont. The cities of Barre and Montpelier currently do not have to meet MS4 permit requirements. Information from the NOAA's 2006 C-CAP Regional Land Cover (https://data.noaa.gov/dataset/dataset/noaas-coastal-change-analysis-program-c-cap-2006-regional-land-cover-data-coastal-united-state1) and the Vermont Center for Geographic Information (https://vcgi.vermont.gov/) were used to characterize land use within each of the nine municipalities in the central and northwestern Vermont, study area, and the partially urbanized Englesby Brook basin located in Burlington and South Burlington, Vermont, that drains into Lake Champlain. The compressed file "EngBrk_ModelArchive.7z" represents the model archive that contains 31 files associated with the Englesby Brook model using the Source Loading and Management Model for Windows (WinSLAMM) version 10.4.0.

The Electronic Cleaning Wipes market has experienced significant growth in recent years, driven by the increasing demand for effective cleaning solutions in various industries, including electronics manufacturing, healthcare, and consumer electronics. These specialized wipes are designed to safely clean sensitive el

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Procurement Analytics Market Size 2025-2029

The procurement analytics market size is forecast to increase by USD 5.81 billion at a CAGR of 19.8% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for cost reduction and efficiency in business operations. Companies are recognizing the value of leveraging data-driven insights to optimize their procurement processes, leading to substantial savings and improved performance. A key trend fueling market expansion is the integration of Artificial Intelligence (AI) and predictive analytics, enabling more accurate forecasting and automated decision-making. However, market growth is tempered by challenges such as data security and privacy concerns, which require robust data protection measures to ensure the confidentiality and integrity of sensitive information. According to data analytics, consumers are increasingly seeking seamless shopping experiences across multiple channels, leading retailers to invest in omnichannel strategies.
To capitalize on market opportunities and navigate challenges effectively, companies must prioritize data security, invest in advanced analytics technologies, and stay informed of regulatory developments. However, the market faces challenges related to procurement, particularly due to increasing environmental regulations and digital paper, and the shift towards digital transformation. By doing so, they can harness the power of procurement analytics to streamline operations, reduce costs, and gain a competitive edge.

What will be the Size of the Procurement Analytics Market during the forecast period?

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In the dynamic market, user experience (UX) plays a pivotal role in driving adoption of advanced data mining tools. Sustainable procurement practices are increasingly integrated into analytics solutions, ensuring data cleansing aligns with social responsibility. Agile methodologies and blockchain technology enable continuous improvement through real-time analytics and predictive modeling. Data visualization tools, custom reports, and interactive dashboards facilitate collaborative analytics, allowing stakeholders to make informed decisions. Procurement maturity models, mobile analytics, and procurement governance ensure data quality management and adherence to best practices. Deep learning and automated decision making streamline processes, while data validation and predictive modeling enhance accuracy.
Role-based access control and change management ensure data security and efficiency. Cloud-based analytics and data enrichment provide scalability and flexibility. Procurement ethics and user interface (UI) design further enhance the value of analytics solutions, ensuring a seamless user experience and ethical decision-making. Overall, the market is evolving to meet the needs of modern businesses, offering innovative solutions for data management and strategic sourcing. Machine learning algorithms optimize supply chain management, enabling retailers to anticipate demand and maintain efficient operations. Digital marketing strategies, including influencer marketing and content marketing, engage customers and drive sales. E-commerce platforms and online retail offer convenience, while virtual reality shopping and augmented reality applications enhance the shopping experience.

How is this Procurement Analytics Industry segmented?

The procurement analytics 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.

Deployment

  On-premises
  Cloud


Business Segment

  Large enterprises
  SMEs


Component

  Solutions
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period. On-premises procurement analytics solutions refer to software systems installed and operated within an organization's data centers or IT infrastructure. These solutions offer businesses complete ownership and control over procurement data, making them suitable for industries with stringent data security, compliance, or customization requirements, such as finance, defense, and government. The primary advantage of on-premises deployment is the ability to deeply customize the system to align with specific organizational processes. Since the solution resides on internal servers, IT teams can tailor features, workflows, and integrations more freely than with most cloud-based options. Data warehousing plays a crucial role in procurement analytics by collecting, storing, and managing large volumes

The Low Pressure Cleaning Truck market is rapidly evolving as industries seek efficient and eco-friendly solutions for their cleaning needs. These specialized vehicles are designed to operate at lower pressure levels, making them ideal for delicate surfaces such as buildings, vehicles, and sensitive equipment. With

The US carpet cleaning industry has faced significant volatility due to turbulent changes in disposable income and consumer confidence. Additional issues have arisen from substantial changes in consumer preferences in the industry. Despite this, the industry has maintained a steady performance in recent years, establishing itself as an essential service for households and businesses. Generating steady revenue over the past five years and home to a remarkably fragmented operator landscape, the industry thrives on routine demand from homeowners seeking healthier living environments and businesses needing spotless spaces. However, competition is fierce, barriers to entry are low and operators, even large franchises like Stanley Steemer, struggle to command a 5 to 6% market share, making local reputation and word-of-mouth recommendations crucial for success. Revenue for the industry has been expanding at a CAGR of 2.6% over the past five years and is expected to reach $6.9 billion in 2025, when revenue will rise by an estimated 1.1%. Despite revenue growth over the past five years, analysis reveals a slowdown and decline in profit margin. Profit has declined from 10.1% in 2020 to 9.6% in 2025, impacted by rising costs and intensifying competition, especially from DIY cleaning solutions and substitute flooring options like hardwood. The demand for eco-friendly and non-toxic cleaning methods has shifted the playing field, as more companies adopt green practices to meet consumer preference shifts. However, this squeezes the margin even more, leading to higher supply and certification expenses. To stay competitive, many operators have added specialized services such as tile, upholstery and air duct cleaning, but the proliferation of DIY cleaning gadgets and online gig platforms has kept traditional carpet cleaning jobs under pressure. In the next five years, forecasts suggest moderate growth with profit margin stabilizing near 9.7%. Companies will continue streamlining operations by embracing energy-efficient equipment and mobile business models. Through 2030, operators will invest in digital marketing, automation and training to meet stricter regulations and evolving health standards, especially in urban and eco-conscious markets. As competition and substitutes continue to challenge the traditional market, businesses that diversify services, scale up green offerings and strengthen local relationships will be best positioned to overcome a maturing, increasingly competitive market. Revenue is forecast to rise at a CAGR of 2.0% over the next five years, reaching $7.6 billion in 2030.

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Server San Market Size 2024-2028

The server san market size is forecast to increase by USD 115.2 billion, at a CAGR of 36.51% between 2023 and 2028.

The market is experiencing significant growth, driven by the increasing adoption of e-commerce platforms and the convergence of server SAN solutions with cloud services. E-commerce websites require robust and efficient data storage solutions to handle large volumes of customer data and transactions. Server SAN technology offers the necessary performance, scalability, and flexibility to meet these demands. Additionally, cloud services are increasingly integrating server SAN solutions to enhance their offerings and provide customers with more options for data storage and management. However, the market faces challenges, primarily in the form of cybersecurity threats. With the increasing digitization of business operations and the growing amount of sensitive data being stored on server SANs, the risk of cyber attacks is heightened. Hackers are constantly seeking vulnerabilities to exploit, and data breaches can result in significant financial and reputational damage. Companies must invest in robust cybersecurity measures to protect their server SAN infrastructure and mitigate these risks. The ability to address these challenges effectively will be crucial for market success.

What will be the Size of the Server San Market during the forecast period?

Request Free SampleThe market continues to evolve, with dynamic market activities unfolding across various sectors. Asset protection remains a top priority, as energy efficiency gains increasing importance in data centers. Server rack cleaning and cable management are essential for operational efficiency and business continuity. Environmental sustainability is a growing concern, with server room sanitation and electrostatic disinfection integral to maintaining air quality and preventing bioaerosol control. Critical environments demand stringent cleanroom protocols and particle control to ensure data center hygiene and data security. Contamination prevention through microbial sampling and HVAC filtration is crucial for IT service continuity and emergency response. Preventive and corrective maintenance schedules are essential for risk mitigation and electrical safety, while adhering to industry standards and compliance regulations. Performance optimization and quality assurance are key objectives, with green data centers and sustainable practices becoming increasingly important. Water conservation and hydrogen peroxide vaporization are among the innovative solutions for IT infrastructure cleaning. Fire suppression and disaster recovery are essential for business continuity, with employee training and best practices ensuring effective implementation of safety procedures. Continuous improvement through performance optimization, antimicrobial coatings, and cost reduction are integral to the market's ongoing evolution. The market's dynamic nature underscores the importance of staying informed and adaptive to emerging trends and regulations.

How is this Server San Industry segmented?

The server san industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeHyperscaleEnterpriseEnd-userLargeSMEsDeployment TypeOn-PremisesCloud-BasedStageFibre ChanneliSCSINVMe-oFFC-NVMeGeographyNorth AmericaUSCanadaEuropeFranceGermanySpainUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanRest of World (ROW)

By Type Insights

The hyperscale segment is estimated to witness significant growth during the forecast period.Hyperscale server Storage Area Network (SAN) solutions have become essential for businesses managing large volumes of data and workloads. These organizations, including cloud providers, social media platforms, e-commerce giants, and other data-intensive enterprises, require storage systems that can effectively scale and perform optimally. Hyperscale server SANs offer the ability to expand storage capacity and performance in response to increasing demand, with a focus on horizontal scaling. Multiple storage nodes are added to the infrastructure to accommodate growing data and workload requirements. Energy efficiency and environmental sustainability are crucial considerations in the design of these solutions. Hyperscale server SANs incorporate advanced power management features and utilize renewable energy sources where possible. Cable management and server room sanitation are essential for maintaining operational efficiency and ensuring business continuity. Environmental monitoring and server downtime reduction are vital aspects of hyperscale server SANs. Real-time monitoring of temperature, humidity, and air quality ensures optimal server performance and reduces the risk of equipment

Food Beverage Disinfection And Cleaning Market size was valued at USD 3,270.8 Million in 2023 and is projected to reach USD 4,879.5 Million by 2031, growing at a CAGR of 5.5% during the forecast period 2024-2031.

Global Food Beverage Disinfection And Cleaning Market Drivers

The market drivers for the Food Beverage Disinfection And Cleaning Market can be influenced by various factors. These may include:

Growing Awareness of Food Safety: With the rising incidence of foodborne illnesses, the awareness around food safety has significantly increased among consumers and businesses. This consciousness drives the demand for effective disinfection and cleaning solutions in food and beverage sectors. Regulatory bodies are imposing stringent standards for sanitation, necessitating advanced cleaning protocols. Consumers are becoming more knowledgeable about hygiene practices, leading to higher expectations from food service providers. Consequently, investing in efficient cleaning and disinfection products becomes a top priority for manufacturers and retailers. This trend fuels market growth as companies seek reliable solutions to maintain safety and quality in food handling. Regulatory Compliance and Standards: Governments and health organizations worldwide have implemented strict regulations concerning hygiene and sanitation in the food and beverage industry. Compliance with these regulations is crucial for brands seeking to maintain market access and uphold consumer trust. Regular inspections and audits emphasize the need for adequate cleaning and disinfection practices throughout the supply chain. The introduction of new standards, such as HACCP (Hazard Analysis Critical Control Point) and GMP (Good Manufacturing Practices), compels businesses to invest in innovative cleaning solutions. Non-compliance can lead to severe penalties, product recalls, and reputational damage, driving demand for disinfection and cleaning products. Technological Advancements: The food and beverage disinfection and cleaning market are witnessing significant technological advancements. Innovations such as automated cleaning systems, advanced surface disinfectants, and eco-friendly cleaning agents are improving the efficacy of cleaning processes. Technologies like ultraviolet (UV) light disinfection and electrostatic sprayers are gaining traction due to their efficiency and ability to cover large areas quickly. The development of smart cleaning systems, which utilize IoT connectivity for monitoring and data collection, is also enhancing operational efficiency. These advancements not only streamline cleaning but also reduce operational costs, making them attractive options for businesses in the industry. Rising Demand for Eco-Friendly Products: Consumer preference is increasingly shifting towards eco-friendly and sustainable practices in the food and beverage sector. As environmental concerns grow, businesses are seeking cleaning and disinfection products that minimize ecological impact. This trend drives research and development to create biodegradable, plant-based, or non-toxic cleaning agents without sacrificing effectiveness. Companies embracing green practices not only comply with consumer preferences but also benefit from potential cost savings and enhanced brand loyalty. The push for sustainability is thus becoming a vital market driver, compelling manufacturers to innovate and adapt their offerings to cater to environmentally conscious consumers. Increasing Global Food Production: As the global population continues to grow, the demand for food production has surged, leading to an increased need for effective cleaning and disinfection solutions. Higher food production levels create extensive supply chains where hygiene plays a critical role in preventing contamination. Both manufacturers and retailers are compelled to adopt stringent cleaning protocols to ensure product safety and quality. The rise in global food trade further amplifies this need, as consistent hygiene practices across borders become essential. This broad demand across various sectors ultimately drives the growth of the food and beverage disinfection and cleaning market, ensuring safety from farm to table.