Alesco's Consumer Database contains demographic information on almost every household in the nation. Nowhere else will you find more complete and accurate information on U.S. households, individuals by name and age, lifestyle interests, hobbies, purchase behavior and ethnicity along with detailed financial-related data including mortgage, wealth and credit attributes. Alesco provides hundreds of selection options to help you target your customers more precisely.

We build the database utilizing hundreds of sources including public records, directories, county recorder and tax assessor files, US Census data, surveys, and purchase transactions. The file is built at both the individual and household levels to provide multiple targeting options. We continuously utilize USPS processing routines to give you the most complete and up-to-date addresses.

Flexible pricing available to meet all your business needs. Data is available on a transactional basis or for yearly licensing with unlimited use cases for marketing and analytics.

Salient Features of Dentists Email Addresses

So make sure that you don’t find excuses for failing at global marketing campaigns and in reaching targeted medical practitioners and healthcare specialists. With our Dentists Email Leads, you will seldom have a reason not to succeed! So make haste and take action today!

1. 1.2 million phone calls per month as a part of a data verification
2. 85% telephone and email verified Dentist Mailing Lists
3. Quarterly SMTP and NCOA verified to keep data fresh and active
4. 15 million verification messages sent every month to validate email addresses
5. Connect with top Dentists across the US, Canada, UK, Europe, EMEA, Australia, APAC and many more countries.
6. egularly updated and cleansed databases to keep it free of duplicate and inaccurate data

How Can Our Dentists Data Help You to Market to Dentists?

We provide a variety of methods for marketing your dental appliances or products to the top-rated dentists in the United States. Take a glance at some of the available channels:

• Email blast • Marketing viability • Test campaigns • Direct mail • Sales leads • Drift campaigns • ABM campaigns • Product launches • B2B marketing

Data Sources

The contact details of your targeted healthcare professionals are compiled from highly credible resources like: • Websites • Medical seminars • Medical records • Trade shows • Medical conferences

What’s in for you? Over choosing us, here are a few advantages we authenticate- • Locate, target, and prospect leads from 170+ countries • Design and execute ABM and multi-channel campaigns • Seamless and smooth pre-and post-sale customer service • Connect with old leads and build a fruitful customer relationship • Analyze the market for product development and sales campaigns • Boost sales and ROI with increased customer acquisition and retention

Our security compliance

We use of globally recognized data laws like –

GDPR, CCPA, ACMA, EDPS, CAN-SPAM and ANTI CAN-SPAM to ensure the privacy and security of our database. We engage certified auditors to validate our security and privacy by providing us with certificates to represent our security compliance.

Our USPs- what makes us your ideal choice?

At DataCaptive™, we strive consistently to improve our services and cater to the needs of businesses around the world while keeping up with industry trends.

• Elaborate data mining from credible sources • 7-tier verification, including manual quality check • Strict adherence to global and local data policies • Guaranteed 95% accuracy or cash-back • Free sample database available on request

Guaranteed benefits of our Dentists email database!

85% email deliverability and 95% accuracy on other data fields

We understand the importance of data accuracy and employ every avenue to keep our database fresh and updated. We execute a multi-step QC process backed by our Patented AI and Machine learning tools to prevent anomalies in consistency and data precision. This cycle repeats every 45 days. Although maintaining 100% accuracy is quite impractical, since data such as email, physical addresses, and phone numbers are subjected to change, we guarantee 85% email deliverability and 95% accuracy on other data points.

100% replacement in case of hard bounces

Every data point is meticulously verified and then re-verified to ensure you get the best. Data Accuracy is paramount in successfully penetrating a new market or working within a familiar one. We are committed to precision. However, in an unlikely event where hard bounces or inaccuracies exceed the guaranteed percentage, we offer replacement with immediate effect. If need be, we even offer credits and/or refunds for inaccurate contacts.

Other promised benefits

• Contacts are for the perpetual usage • The database comprises consent-based opt-in contacts only • The list is free of duplicate contacts and generic emails • Round-the-clock customer service assistance • 360-degree database solutions

McGRAW provides over 3.5 million high-performing Medicare leads, helping companies connect with seniors 65 and older during all enrollment periods. Our real-time and aged leads ensure meaningful Medicare conversations year-round, as well as, premium senior lists for targeted marketing.

This publication provides statistics on the number of unique NHS numbers with an associated national data opt-out. The national data opt-out was introduced on 25 May 2018. It was introduced following recommendations from the National Data Guardian. It indicates that a patient does not want their confidential patient information to be shared for purposes beyond their individual care across the health and care system in England. The service allows individuals to set a national data opt-out or reverse a previously set opt-out. It replaced the previous type 2 opt-outs which patients registered via their GP Practice. Previous type 2 opt-outs have been converted to national data opt-outs each month, until November 2018. This is why the monthly increase in opt-outs decreases from December 2018 onward. This publication includes the number of people who have a national data opt-out, broken down by age, gender and a variety of geographical breakdowns. From June 2020 the methodology for reporting NDOP changed, representing a break in time series. Therefore, caution should be used when comparing data to publications prior to June 2020. The number of deceased people with an active NDOP has been captured and reported for the first time in June 2020. Please note that this publication is no longer released monthly. It is released annually or when the national opt-out rate changes by more than 0.1 per cent. Prior to September 2020 there is a slight inflation of less than 0.05 percent in the number of National Data Opt-outs. This is due to an issue with the data processing, which has been resolved and does not affect data after September 2020. This issue does not disproportionately affect any single breakdown, including geographies. Please take this into consideration when using the data. As of January 2023, index of multiple deprivation (IMD) data has been added to the publication, allowing the total number of opt-outs to be grouped by IMD decile. This data has been included as a new CSV, and has also been added to a new table in the summary file. IMD measures relative deprivation in small areas in England, with decile 1 representing the most deprived areas, and decile 10 representing least deprived. Please note that the figures reported in IMD decile tables will not add up to the national totals. This is because the IMD-LSOA mapping reference data was created in 2019, and any geography codes added since then will not be mapped to an IMD decile. For more information about the reference data used, please view this report: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 Management information describes aggregate information collated and used in the normal course of business to inform operational delivery, policy development or the management of organisational performance. It is usually based on administrative data but can also be a product of survey data. We publish these management information to ensure equality of access and provide wider public value.

ATTENTION USERS Some Providers' Opt-Out Status may end early due to COVID 19 waivers. Please contact your respective MAC for further information. For more information on the opt-out process, see Manage Your Enrollment or view the FAQ section below. The Opt Out Affidavits dataset provides information on providers who have decided not to participate in Medicare. It contains provider's NPI, specialty, address, and effective dates.

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

Core Database Statistics

Consumer Records: Over 269 million

Email Addresses: Over 160 million (verified and deliverable)

Phone Numbers: Over 76 million (mobile and landline)

Mailing Addresses: Over 116,000,000 (NCOA processed)

Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

Multi-Channel Campaign Applications

Deploy across all major marketing channels:

Email marketing and automation

Social media advertising

Search and display advertising (Google, YouTube)

Direct mail and print campaigns

Telemarketing and SMS campaigns

Programmatic advertising platforms

Data Quality & Sources

Our consumer data aggregates from multiple verified sources:

Public records and government databases

Opt-in subscription services and registrations

Purchase transaction data from retail partners

Survey participation and research studies

Online behavioral data (privacy compliant)

Technical Delivery Options

File Formats: CSV, Excel, JSON, XML formats available

Delivery Methods: Secure FTP, API integration, direct download

Processing: Real-time NCOA, email validation, phone verification

Custom Selections: 1,000+ selectable demographic and behavioral attributes

Minimum Orders: Flexible based on targeting complexity

Unique Value Propositions

Dual Spouse Targeting: Reach both household decision-makers for maximum impact

Cross-Platform Integration: Seamless deployment to major ad platforms

Real-Time Updates: Monthly data refreshes ensure maximum accuracy

Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

Compliance Management: Built-in opt-out and suppression list management

Ideal Customer Profiles

E-commerce retailers seeking customer acquisition

Financial services companies targeting specific demographics

Healthcare organizations with compliant marketing needs

Automotive dealers and service providers

Home improvement and real estate professionals

Insurance companies and agents

Subscription services and SaaS providers

Performance Optimization Features

Lookalike Modeling: Create audiences similar to your best customers

Predictive Scoring: Identify high-value prospects using AI algorithms

Campaign Attribution: Track performance across multiple touchpoints

A/B Testing Support: Split audiences for campaign optimization

Suppression Management: Automatic opt-out and DNC compliance

Pricing & Volume Options

Flexible pricing structures accommodate businesses of all sizes:

Pay-per-record for small campaigns

Volume discounts for large deployments

Subscription models for ongoing campaigns

Custom enterprise pricing for high-volume users

Data Compliance & Privacy

VIA.tools maintains industry-leading compliance standards:

CCPA (California Consumer Privacy Act) compliant

CAN-SPAM Act adherence for email marketing

TCPA compliance for phone and SMS campaigns

Regular privacy audits and data governance reviews

Transparent opt-out and data deletion processes

Getting Started

Our data specialists work with you to:

1. Define your target audience criteria

2. Recommend optimal data selections

3. Provide sample data for testing

4. Configure delivery methods and formats

5. Implement ongoing campaign optimization

Why We Lead the Industry

With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

App Tracking Transparency Key StatisticsATT Opt-In Rate by App CategoryATT Opt-In Rate by Game CategoryATT Opt-In Rate by CountryiOS Apps User TrackingiOS Apps Background Location AccessiOS Apps...

SQL In-Memory Database Market size was valued at USD 9.26 Billion in 2024 and is projected to reach USD 35.7 Billion by 2032, growing at a CAGR of 20.27% from 2026 to 2032.

SQL In-Memory Database Market Drivers

Demand for Real-Time Analytics and Processing: Businesses increasingly require real-time insights from their data to make faster and more informed decisions. SQL In-Memory databases excel at processing data much faster than traditional disk-based databases, enabling real-time analytics and operational dashboards.

Growth of Big Data and IoT Applications: The rise of Big Data and the Internet of Things (IoT) generates massive amounts of data that needs to be processed quickly. SQL In-Memory databases can handle these high-velocity data streams efficiently due to their in-memory architecture.

Improved Performance for Transaction Processing Systems (TPS): In-memory databases offer significantly faster query processing times compared to traditional databases. This translates to improved performance for transaction-intensive applications like online banking, e-commerce platforms, and stock trading systems.

Reduced Hardware Costs (in some cases): While implementing an in-memory database might require an initial investment in additional RAM, it can potentially reduce reliance on expensive high-performance storage solutions in specific scenarios.

Focus on User Experience and Application Responsiveness: In today's digital landscape, fast and responsive applications are crucial. SQL In-Memory databases contribute to a smoother user experience by enabling quicker data retrieval and transaction processing.

However, it's important to consider some factors that might influence market dynamics:

Limited Data Capacity: In-memory databases are typically limited by the amount of available RAM, making them less suitable for storing massive datasets compared to traditional disk-based solutions.

Higher Implementation Costs: Setting up and maintaining an in-memory database can be more expensive due to the additional RAM requirements compared to traditional databases.

Hybrid Solutions: Many organizations opt for hybrid database solutions that combine in-memory and disk-based storage, leveraging the strengths of both for different data sets and applications.

Alesco Data's Automotive records are updated monthly from millions of proprietary sourced vehicle transactions. These incoming transactions are processed through compilation rules and are either added as new, incremental records to our file, or contribute to validating existing records.

Our recent focus is on compiling new vehicle ownership, and the file includes over 14.2 million late model vehicle owners (2020-2025).

We also append our Persistent ID, telephone numbers, and demographics for a complete file that can support your direct mail and email marketing campaigns, lead validation, and identity verification needs. A Persistent ID is assigned to each vehicle record and tracks consumers as they change addresses or phone numbers, and vehicles as they change owners.

The database is not derived from state motor vehicle databases and therefore not subject to the Shelby Act also known as the Driver's Privacy Protection Act (DPPA) of 2000. The data is deterministic and sources include sales and service data, warranty data and notifications, aftermarket repair and maintenance facilities, and scheduled maintenance records.

Fields Included: Make Model Year VIN Data Vehicle Class Code (crossover, SUV, full-size, mid-size, small) Vehicle Fuel Code (gas, flex, hybrid) Vehicle Style Code (sport, pickup, utility, sedan) Mileage Number of Vehicles per Household First seen date Last seen date Email

In April 2021, Apple released its iOS 14.5 version, introducing the App Tracking Transparency (ATT) framework, which gives users the freedom to enable or disable tracking. According to data gathered in March 2022, the overall ATT opt-in rate by iOS users worldwide was 46 percent. Finance and utilities apps had a higher ATT opt-in rate compared to the overall figure, with a 53 percent rate, respectively. In comparison, education apps, as well as health and fitness apps had a lower opt-in rate, with 41 percent and 42 percent of global users opting in via iOS ATT in the examined month.

iOS App developers adapt to the ATT During the third quarter of 2021, 80 percent of iOS users took advantage of the new possibility given by Apple’s ATT framework and decided to opt-out of tracking while using several social media platforms on their mobile devices. This resulted in 40 percent of advertising impressions being lost for advertisers on Facebook, YouTube, and Twitter. According to a survey of app publishers, as of November 2021, a large part of respondents considered it was “too early” to tell if Apple’s ATT could cause a drop in advertising revenues in the app market. In 2022, the impact of Apple’s ATT was revealed when Meta reported slowing revenue growth and identified changes in the iOS framework as one of the causes behind the trend.

App privacy: what users want As seen from the immediate adoption of Apple’s App Tracking framework from U.S. users in one of iOS regional strongholds, when it comes to app privacy, mobile users appear to want the privilege of choosing to share their data or not. Additionally, almost five in 10 Android users reported that their main reason for switching to devices powered by the iOS operating system would be for better data protection. Android users might not have to buy a new iPhone after all, as Google announced in February 2022 its project ‘Privacy Sandbox.’ The initiative will see users gaining more control over their data and possible major restructuring around the use of advertising ID.

The City of Bloomington contracted with National Research Center, Inc. to conduct the 2017 Bloomington Community Survey. This was the first time a scientific citywide survey had been completed covering resident opinions on service delivery satisfaction by the City of Bloomington and quality of life issues. This is the opt-in companion to that scientific survey. The statistically valid and representative survey results are available at https://bloomington.data.socrata.com/dataset/Community-Survey-2017-Survey-Data/p8uv-cjhr An additional 1,435 residents completed an opt-in survey online. The data in this collection is opt-in data and is provided in the interest of transparency. It is not recommended for analysis. The statistically valid and representative survey results are available at https://bloomington.data.socrata.com/stories/s/bsc2-z6t2

The Bus Breakdown and Delay system collects information from school bus vendors operating out in the field in real time. Bus staff that encounter delays during the route are instructed to radio the dispatcher at the bus vendor’s central office. The bus vendor staff are then instructed to log into the Bus Breakdown and Delay system to record the event and notify OPT. OPT customer service agents use this system to inform parents who call with questions regarding bus service. The Bus Breakdown and Delay system is publicly accessible and contains real time updates. All information in the system is entered by school bus vendor staff.

This is the authoritative public subset of the compiled Minnesota statewide parcel dataset. By authoritative, we mean this is the official source of statewide parcel data compiled from the counties that have opted-in to be included. Counties are the authoritative source and owner of parcel data. Quarterly, MnGeo compiles and standardizes the county data using the Minnesota Geospatial Advisory Council's parcel data standard. In the compilation process, some data content is standardized or otherwise modified (capitalization and address parsing are the most common changes). The full opt-in compiled parcel metadata record can be found on the Minnesota Geospatial Commons.To obtain the most current and authoritative data in its original form, users are referred back to the respective county. Links to each county's downloadable and/or web-viewable data, where known, are available in the accompanying spatial metadata dataset.Known limitations:Data provided by counties are often limited to a subset of fields and may not be the same fields across all counties. The fields provided by a given county may change by quarter.The USECLASS and XUSECLASS fields, while often consistent within a county, are not standardized between counties.The OWN_ADDR_# and TAX_ADDR_# fields are often populated in ways not consistent with the standard. In particular, an address number/street address may not be in Line 1, and city/state/zip cannot be relied on to be in Line 3. Even within a single county, the city/state/zip line may not be in a consistent field.Parcels with addresses on fractional streets (5-1/2th Ave) cause issues for our address parser when parsing is needed for aggregation and may be missing some or all of the address data. Certain other oddly named streets can also cause this behavior.A maximum record count has been set on the mapping service. This limits the number of features that can be returned in a single request. It is set to balance usability and response time.

Cloud-based Database Market Outlook

In 2023, the global cloud-based database market size was estimated to be approximately USD 15.5 billion, with projections indicating robust growth to around USD 39.1 billion by 2032, reflecting a compound annual growth rate (CAGR) of 11.0%. This impressive growth trajectory can be attributed to several critical growth factors. The increasing adoption of cloud technologies across various industries, the growing need for scalable and flexible data storage solutions, and the rising awareness of the benefits associated with cloud-based databases are fueling this expansion. Furthermore, businesses are increasingly migrating their on-premises databases to the cloud to enhance operational efficiency, reduce costs, and gain competitive advantages, thus driving the demand for cloud-based databases.

The rapid digital transformation across multiple sectors serves as a significant catalyst for the expansion of the cloud-based database market. Enterprises are increasingly relying on data-driven strategies to enhance their decision-making processes and improve customer experiences. With the proliferation of digital data, organizations are in dire need of efficient data management solutions that can handle large volumes of data with ease. Cloud-based databases offer the perfect solution, providing scalability, flexibility, and real-time access to data, which are crucial in today's fast-paced business environment. Additionally, the emergence of Internet of Things (IoT) devices, artificial intelligence (AI), and big data analytics further propels the demand for cloud databases, as these technologies require robust and flexible data management platforms.

Another vital growth factor is the increasing adoption of hybrid and multi-cloud strategies by organizations worldwide. Companies are no longer reliant on a single cloud provider; instead, they are leveraging multiple platforms to optimize performance, reduce latency, and ensure data backup and recovery. This trend is particularly prominent among large enterprises seeking to enhance their global reach and improve service delivery. The flexibility offered by cloud-based databases supports these strategies by enabling seamless data integration and management across various cloud environments. Moreover, the growing emphasis on cloud-native application development further aligns with the adoption of cloud-based databases, as they provide the necessary infrastructure and tools to support modern application architectures.

Security and compliance concerns have always been a significant consideration for enterprises moving to the cloud. However, advancements in cloud security and the introduction of stringent data protection regulations like GDPR and CCPA have alleviated some of these apprehensions. Cloud service providers are continuously investing in enhancing their security offerings, providing robust encryption, access controls, and compliance certifications to their clients. This, in turn, boosts the confidence of organizations in adopting cloud-based databases, knowing that their data is secure and compliant with industry standards. As businesses increasingly recognize the security advantages offered by cloud platforms, this further accelerates the market's growth.

Regionally, North America is expected to be a dominant player in the cloud-based database market, driven by early adoption of cloud technologies and the presence of major cloud service providers. Europe is also witnessing significant growth, with enterprises in countries like the UK, Germany, and France increasingly shifting towards cloud solutions. The Asia Pacific region is anticipated to experience the highest growth rate, fueled by rapid digitalization and increasing IT investments in countries such as China, India, and Japan. Latin America and the Middle East & Africa are gradually catching up, with businesses recognizing the potential of cloud-based databases in improving operational efficiencies and driving innovation.

Database Type Analysis

When it comes to database types, the market is primarily segmented into SQL and NoSQL databases. SQL databases have been the traditional choice for structured data storage and management, and they continue to hold a significant share of the market. Organizations opt for SQL databases due to their robust support for complex queries, ACID compliance, and established presence in the enterprise IT landscape. The consistent demand for SQL databases can be attributed to their ability to handle transactional data and their widespread use in various applications, including enterprise resource planning (ERP) and customer relation

This data set contains NASA DC-8 Langley Aerosol Research Group Experiment (LARGE) Optical Parameter files (OPT) Data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.

Replication data and R script.. Visit https://dataone.org/datasets/sha256%3A5ab3f7558eb6f33fe3d225dc46acfd62fd68f019ffbba257d0c1f37143c0c217 for complete metadata about this dataset.

This dataset is a compilation of county parcel data from Minnesota counties that have opted-in for their parcel data to be included in this dataset.

It includes the following 55 counties that have opted-in as of the publication date of this dataset: Aitkin, Anoka, Becker, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Fillmore, Grant, Hennepin, Houston, Isanti, Itasca, Jackson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Mille Lacs, Morrison, Mower, Murray, Norman, Olmsted, Otter Tail, Pennington, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Saint Louis, Scott, Sherburne, Stearns, Stevens, Traverse, Waseca, Washington, Wilkin, Winona, Wright, and Yellow Medicine.

If you represent a county not included in this dataset and would like to opt-in, please contact Heather Albrecht (Heather.Albrecht@hennepin.us), co-chair of the Minnesota Geospatial Advisory Council (GAC)’s Parcels and Land Records Committee's Open Data Subcommittee. County parcel data does not need to be in the GAC parcel data standard to be included. MnGeo will map the county fields to the GAC standard.

County parcel data records have been assembled into a single dataset with a common coordinate system (UTM Zone 15) and common attribute schema. The county parcel data attributes have been mapped to the GAC parcel data standard for Minnesota: https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

This compiled parcel dataset was created using Python code developed by Minnesota state agency GIS professionals, and represents a best effort to map individual county source file attributes into the common attribute schema of the GAC parcel data standard. The attributes from counties are mapped to the most appropriate destination column. In some cases, the county source files included attributes that were not mapped to the GAC standard. Additionally, some county attribute fields were parsed and mapped to multiple GAC standard fields, such as a single line address. Each quarter, MnGeo provides a text file to counties that shows how county fields are mapped to the GAC standard. Additionally, this text file shows the fields that are not mapped to the standard and those that are parsed. If a county shares changes to how their data should be mapped, MnGeo updates the compilation. If you represent a county and would like to update how MnGeo is mapping your county attribute fields to this compiled dataset, please contact us.

This dataset is a snapshot of parcel data, and the source date of the county data may vary. Users should consult County websites to see the most up-to-date and complete parcel data.

There have been recent changes in date/time fields, and their processing, introduced by our software vendor. In some cases, this has resulted in date fields being empty. We are aware of the issue and are working to correct it for future parcel data releases.

The State of Minnesota makes no representation or warranties, express or implied, with respect to the use or reuse of data provided herewith, regardless of its format or the means of its transmission. THE DATA IS PROVIDED “AS IS” WITH NO GUARANTEE OR REPRESENTATION ABOUT THE ACCURACY, CURRENCY, SUITABILITY, PERFORMANCE, MECHANTABILITY, RELIABILITY OR FITINESS OF THIS DATA FOR ANY PARTICULAR PURPOSE. This dataset is NOT suitable for accurate boundary determination. Contact a licensed land surveyor if you have questions about boundary determinations.

DOWNLOAD NOTES: This dataset is only provided in Esri File Geodatabase and OGC GeoPackage formats. A shapefile is not available because the size of the dataset exceeds the limit for that format. The distribution version of the fgdb is compressed to help reduce the data footprint. QGIS users should consider using the Geopackage format for better results.

McGRAW offers 1.6 million high-quality opt-in home warranty leads that connect providers with homeowners actively seeking warranty solutions. Our real-time and aged leads come from exclusive, non-incentivized leads tailored for effective outreach and scalable solutions.

The dataset contains Academic-year-wise historically compiled data on the total number of International Students who have enrolled in Undergraduate, Graduate, Non-Degree and Optional Practical Training (OPT) courses in the United States of America (USA). The time period of data availability is every five years for the period from 1954-55 to 1979-80 and every year from the year 1979-80 onwards.

The latest Apple iOS version includes a new privacy feature, which means that mobile apps are forced to ask users for permission to allow them to collect tracking data. Among those that have already installed the iOS 14.5 update, the opt-in rate (how many people are choosing to allow app tracking) is around ** percent, as of April 2022. With so many users concerned about their online activities being tracked, a low opt-in rate had been predicted.