Access a comprehensive and continuously updated database of all companies and entities registered in the U.S. government’s System for Award Management (SAM). This dataset is refreshed daily to ensure accuracy and includes detailed information on each company’s registration status, business type, and federal contracting eligibility.

The dataset features:

Company Profiles: Legal name, DUNS/UEI identifiers, and registration details.

Primary & Secondary NAICS Codes: Industry classification for federal contracting opportunities.

PSC (Product Service Codes): Government-focused categorization of products and services.

Points of Contact: Key employee information for business development and outreach.

Small Business Designations: 8(a), HUBZone, SDVOSB, WOSB, and other SBA certifications.

Status Tracking: Active vs. inactive registrations and expiration dates.

This dataset is ideal for federal contractors, market researchers, business development teams, and solution providers seeking to identify, segment, and engage with government-registered businesses. With daily updates, you can be confident you are working with the most current and complete federal vendor information available.

The Small Business Administration maintains the Dynamic Small Business Search (DSBS) database. As a small business registers in the System for Award Management, there is an opportunity to fill out the small business profile. The information provided populates DSBS. DSBS is another tool contracting officers use to identify potential small business contractors for upcoming contracting opportunities. Small businesses can also use DSBS to identify other small businesses for teaming and joint venturing.

Listing of all active businesses currently registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly. NAICS Codes are from 2007 NAICS: https://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2007

This data contains the latest State and Local Government Finance data from the U.S. Census. A detailed description of the project can be found in: Pierson K., Hand M., and Thompson F. (2015). The Government Finance Database: A Common Resource for Quantitative Research in Public Financial Analysis. PLoS ONE doi: 10.1371/journal.pone.0130119

The English Business Survey (EBS) is commissioned by the Department for Business, Innovation and Skills (BIS) to provide a monthly assessment of business perceptions of current, past and expected economic and business conditions in each English region. A detailed understanding of businesses' perceptions and plans across England will inform the Government's economic growth and rebalancing agenda.

The sample for the EBS is drawn from the Inter-departmental Business Register (IDBR). The primary objective is to achieve a sample that is as close as possible to being proportionate to the employment distribution within England. The EBS is conducted at the level of the workplace (i.e. individual sites within an enterprise, such as a factory, shop or office) rather than at the level of the business or enterprise. The sample is therefore selected at this level as well. The sample of workplaces is selected from across all industry sectors, including public sector and not-for-profit organisations.

Further information on the EBS and monthly statistical releases derived from the survey can be found on the BIS English Business Survey website.

Linking to other business studies These data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

The majority of observations only contain IDBR plant identifiers (LUref). Therefore, it may not be possible to ascertain plants that belong to the same enterprise. Therefore, we recommend that users also apply for access to the Business Structure Database (SN 6697), which will allow users to link observations to their parent enterprises. The survey provides information on current business conditions compared with three months ago and expectations for three months ahead. The survey includes variables relating to:business characteristicsoutput, including domestic outputexportsstocksemployment and labour costscapitalinput and output pricescredit conditionsinvestment, including capital investmentbusiness performanceLocal Enterprise Partnerships (private sector only)

UK Postcode-level Flood Risk Data (Rivers and Sea)

Identifying Risk Areas for Flood Protection and Planning

By IBM Watson AI XPRIZE - Environment [source]

About this dataset

Welcome to the UK Postcode-level Flood Risk Dataset. This open source dataset contains detailed information on flood risk levels by postcode in the UK, allowing you to map out potential problems and plan accordingly. With this dataset, you can assess each postcode's growing risk of floods due to human land use change and climate change-related weather patterns, as well as historical occurrences specific to each area.

We pull data from organizations including Risk of Flooding from Rivers & Sea, Open Postcode Geo, Royal Mail copyright & database right (2017), National Statistics data Crown copyright & database right (2017), and Environment Agency data licensed under the Open Government Licence v3.0. The associated columns in this dataset are detailed below:

• Postcode - unique identifier for the postal code district where flood risk area is located
• FID - Unique ID for each location point
• PROB 4BAND - Flood risk level for a given postcode determined according to a four tier grade system (High, Medium, Low or Very Low)
• SUITABILITY - Suitability of location based on environment factors assessed according to OFRA criteria
• PUB_DATE - Date when data was published or last updated
• RISK FOR INSURANCE SOP - Standard Operating Procedure assigned according the Probability 4 band Risk rating
• Easting/Northing/Latitude/Longitude – Coordinates associated with a given postcode location

This data can be used by local authorities and agencies conducting flood mapping projects; insurers assessing assets at specified locations using an agreed set of methodology; advisors assessing locations for development purposes; forecasters aiding contingency planning; homeowners/commercial businesses seeking insurance cover for claims arising from flooding events etc. Ultimately we hope citizens around the world use this dataset as an important tool to predict areas exposedto potential flooding risks so that preventive measures may be taken beforehand!

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How to use the dataset

This Kaggle dataset provides postcode-level flood risk data for the UK, including the flood risk level, coordinates, and other related information. This dataset is derived from Risk of Flooding from Rivers and Sea (provided by the British government) and Open Postcode Geo. It is licensed under the OGL 3.0 open government license.

In this data set you will find columns for each postcode as well as unique identifiers for a particular region (FID), an overall four band flood risk level (PROB_4BAND), whether a specific location or building is suitable or not (SUITABILITY), when it was published so you can be sure you are getting reliable up to date information (PUB_DATE), Easting/Northing which roughly measure distance eastwards/northwards of locations in meters(EASTING / NORTHING), LATITUDE & LONGITUDE that point to a precise location on google map & finally RISK_FOR_INSURANCE SOP which clearly distinguishes between sites which should generate warnings with regard to various kinds of insurance policies. This allows companies applying digital transformation solutions like hazard mapping solutions to show what risks certain locations present in relation to possible flood damage using digital technologies such as GIS systems or location intelligence tools etc., allowing organizations apply data science models or techniques like predictive analytics that may be used in decision making processes such as those taken by municipalities when signing off disaster management plans etc..

You can use this dataset for research purposes, share your findings on websites through charts & graphs to develop an educational understanding about possible hazards associated with areas that people inhabit around UK particularly at times when storm systems are localized heavily over specific regions making it most likely due causing major catastrophic event across British Isles . People living there can always access their respective postcodes very easily via our Flood Map by Postcode page here Flood Map.

When writing reports acknowledging source material properly , kindly take into account our acknowledgements including; Contains OS data © Crown copyright and database right 2017, Contains Royal Mail data © Royal Mail copyright and Database right 2017 , Contains National Statistics ...

The datasets include the following:

Businesses - License Types:

• Collection Agency
• Consumer Reporting Agency
• Distributor (Area: Province of Ontario)
• Lender
• Loan Broker
• Bailiff (Business)

Individuals - License Types:

• Bailiff (Assistant - Reg)
• Personal Information Investigator
• Bailiff (Owner)
• Bailiff (Assistant - Appointed)
• Bailiff (Employee)

"https://www.consumerbeware.mgs.gov.on.ca/esearch/start.do">Search the database.

Using our intelligently designed data dashboard, you can quickly understand how General Electric Company (GE) is lobbying the U.S. government, how much they're spending on it, and most importantly - the bills and specific issues on which they lobby.

Gain an informational edge over the market with our Lobbying Data Intelligence Platform. Search for, filter through, and download data from any period of recorded American lobbying history (1999-present). Perform analysis by company, lobbyist, lobbying firm, government agency, or issue.

For lobbying firms: understand your competitors. Understand who is registering with who. Gain insight on quarterly reports and specific issues other firms are lobbying on.

Our lobbying data is collected and aggregated from the U.S. Senate Office of Public Records from 1999-present and is updated on a regular basis. We utilize advanced data science techniques to ensure accurate data points are collected and ingested, match similar entities across time, and tickerize publicly traded companies that lobby.

Our comprehensive and advanced lobbying database is completed with all the information you need, with more than 1.6 million lobbying contracts ready-for-analysis. We include detailed information on all aspects of federal lobbying, including the following fascinating attributes, among much more:

1. Clients: The publicly traded company, privately owned company, interest group, NGO, or state or local government that employs or retains a lobbyist or lobbying firm.

2. Registrants (Lobbying Firms): Either the name of the lobbying firm hired by the client, or the name of the client if the client employs in-house lobbyists.

3. Lobbyists: The names and past government work experience of the individual lobbyists working on a lobbying contract.

4. General Issues: The general issues for which clients lobby on (ex: ENV - Environment, TOB - Tobacco, FAM - Family Issues/Abortion).

5. Specific Issues: A long text description of the exact bills and specific issues for which clients lobby on.

6. Bills Lobbied On: A parsed version of Specific Issues that catches specific HR, PL, and ACTS lobbied on (ex: H.R. 2347, S. 1117, Tax Cuts and Jobs Act).

7. Agencies Lobbied: The names of one or more of 250+ government agencies lobbied on in the contract (ex: White House, FDA, DOD).

8. Foreign Entities: The names and origin countries of entities affiliated with the client (ex: BNP Paribas: France).

Gain access to our highly unique and actionable U.S. lobbying database. Further information on LobbyingData.com and our alternative datasets and database can be found on our website, or by contacting us through Datarade.

Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data.

From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.

G-NAF Core will be updated on a quarterly basis along with G-NAF.

Further information about contributors to G-NAF is available here.

With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.

Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Changes in the November 2025 release

• Nationally, the November 2025 update of G-NAF shows an increase of 32,773 addresses overall (0.21%). The total number of addresses in G-NAF now stands at 15,827,416 of which 14,983,358 or 94.67% are principal.

• There is one new locality for the November 2025 Release of G-NAF, the locality of Southwark in South Australia.

• Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.

Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.

Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

License Information

Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)

The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.

The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.

End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

Preferred attribution for Adapted Material:

Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

What to Expect When You Download G-NAF

G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.

All organisations hold information about the core of their business. Forestry England holds information on trees and forests. We use this information to help us run our business and make decisions. The role of the Forest Inventory (the Sub-compartment Database (SCDB) and the stock maps) is to be our authoritative data source, giving us information for recording, monitoring, analysis and reporting. Through this it supports decision-making on the whole of the FE estate. Information from the Inventory is used by FE, wider government, industry and the public for economic, environmental and social forest-related decision-making. Furthermore, it supports forest-related national policy development and government initiatives, and helps us meet our national and international forest-related reporting responsibilities. Information on our current forest resource, and the future expansion and availability of wood products from our forests, is vital for planners both in and outside FE. It is used when looking at the development of processing industries, regional infrastructure, the effect upon communities of our actions, and to prepare and monitor government policies. The Inventory (SCDB and stock maps), with ‘Future Forest Structure’ and the ‘rollback’ functionality of Forester, will help provide a definitive measure of trends in extent, structure, composition, health, status, use, and management of all FE land holdings. We require this to meet national and international commitments, to report on the sustainable management of forests as well as to help us through the process of business and Forest Design Planning. As well as helping with the above, the SCDB helps us address detailed requests from industry, government, non-government organisations and the public for information on our estate. FE's growing national and international responsibilities and the requirements for monitoring and reporting on a range of forest statistics have highlighted the technical challenges we face in providing consistent, national level data. A well kept and managed SCDB and GIS (Geographical Information System - Forester) will provide the best solution for this and assist countries in evidence-based policy making. Looking ahead at international reporting commitments; one example of an area where requirements look set to increase will be reporting on our work to combat climate change and how our estate contributes to carbon sequestration. We have put in place processes to ensure that at least the basics of our inventory are covered: The inventory of forests; The land-uses; The land we own ( Deeds); The roads we manage. We depend on others to allow us to manage the forests and to provide us with funds and in doing so we need to be seen to be responsible and accountable for our actions. A foundation of achieving this is good record keeping. A subcompartment should be recognisable on the ground. It will be similar enough in land use, species or habitat composition, yield class, age, condition, thinning history etc. to be treated as a single unit. They will generally be contiguous in nature and will not be split by roads, rivers, open space etc. Distinct boundaries are required, and these will often change as crops are felled, thinned, replanted and resurveyed. In some parts of the country foresters used historical and topographical features to delineate subcompartment boundaries, such as hedges, walls and escarpments. In other areas no account of the history and topography of the site was taken, with field boundaries, hedges, walls, streams etc. being subsumed into the sub-compartment. Also, these features may or may not appear on the OS backdrop, again this was dependent on the staff involved and what they felt was relevant to the map. The main point is that, as managers we may find such obvious features in the middle of a subcompartment when nothing is indicated on the stock map, while the same thing would be indicated elsewhere. Attributes; FOREST Cost centre Nos. COMPTMENT Compartment Nos. SUBCOMPT Sub-compartment letter BLOCK Block nos. CULTCODE Cultivation Code CULTIVATN Cultivation PRIHABCODE Primary Habitat Code PRIHABITAT Primary Habitat PRILANDUSE Land Use of primary component PRISPECIES Primary component tree species PRI_PLYEAR prim. component year planted PRIPCTAREA Prim. component %Area of sub-compartment SECHABCODE Secondary Habitat Code SECHABITAT Secondary Habitat SECLANDUSE Land Use of secondary component SECSPECIES Secondary component tree species SEC_PLYEAR Secondary component year planted SECPCTAREA Secondary component %Area of sub-compartment TERLANDUSE Land Use of tertiary component TERSPECIES Tertiary component tree species TER_PLYEAR Tertiary component year planted TERPCTAREA Tertiary component %Area of sub-compartment TERHABITAT Tertiary Habitat TERHABCODE Tertiary Habitat Code. Any maps produced using this data should contain the following Forestry Commission acknowledgement: “Contains, or is based on, information supplied by the Forestry Commission. © Crown copyright and database right 2025 Ordnance Survey AC0000814847”. Attribution statement: © Forestry Commission copyright and/or database right 2025. All rights reserved. Contains OS data © Crown copyright and database right 2025.

This dataset, compiled by NREL using data from ABB, the Velocity Suite (http://energymarketintel.com/) and the U.S. Energy Information Administration dataset 861 (http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity rates with likely zip codes for both investor owned utilities (IOU) and non-investor owned utilities. Note: the files include average rates for each utility (not average rates per zip code), but not the detailed rate structure data found in the OpenEI U.S. Utility Rate Database (https://openei.org/apps/USURDB/).

Lithuania number dataset is a database of phone numbers collected from trusted sources. This means the numbers come from reliable places like government records, websites, or phone companies. The companies that provide this data work hard to ensure it is correct. They even offer source URLs, so you can see where the data came from. Moreover, you get 24/7 support, so if you have questions, help is always available. List to Data is a helpful website for finding important cell numbers quickly. Additionally, the phone numbers in the Lithuania number dataset follow an opt-in system. This means people agreed to share their phone numbers. This system is important because it keeps the data legal. It ensures that you are only contacting people who have given permission. Number data in Lithuania makes it easy to connect with the right people. Lithuania phone data is a special set of phone numbers that you can filter to meet your needs. You can easily filter the list by gender, age, and relationship status. For example, you can quickly sort the data to contact older adults or young singles easily. This flexibility makes it easier to communicate with the right audience. Therefore, you can connect with the people you want to reach. Also, the Lithuanian phone data follows strict GDPR rules. These rules protect people’s privacy and make sure their information stays safe. We collect and use the database of Lithuania in ways that respect everyone’s rights. Additionally, it removes any invalid numbers. You can find important phone numbers easily on our website, List to Data. Lithuania phone number list is a collection of phone numbers from people living in Lithuania. This list is completely correct and valid, meaning all numbers work properly. Companies check every phone number to ensure it is accurate. If you find a number that doesn’t work, you can get a new one for free. Moreover, Lithuania phone number list is about all numbers from authorized customers. People on this list agreed to share their numbers. As a result, you can use the data without worrying about legal issues. This makes the phonebook safe and useful for businesses that want to connect with people in Lithuania.

The Social Policy Simulation Database and Model (SPSD/M) is a micro computer-based product designed to assist those interested in analyzing the financial interactions of governments and individuals in Canada. It can help one to assess the cost implications or income redistributive effects of changes in the personal taxation and cash transfer system. The SPSD is a non-confidential, statistically representative database of Canadian individuals in their family context, with enough information on each individual to compute taxes paid to and cash transfers received from government. The SPSM is a static accounting model which processes each individual and family on the SPSD/M, calculates Canadian federal and provincial taxes and transfers using legislated or proposed programs and algorithms, and reports on the results. It gives the user a high degree of control over the inputs and outputs to the model and can allow the user to modify existing tax/transfer programs or test proposals for entirely new programs. The model can be run using a visual interface and it comes with full documentation. Caution: This tool is specifically designed for analyzing the tax and transfer policies in Canada and cannot be used to analyze policies for other countries.

The enterprise aid database, set up by the Government as part of the simplification programme for enterprises, is the reference database on public financial aid for entrepreneurs and project leaders. This common base of information on aid to companies brings together both national and territorial public funders, with whom updating processes are developed in order to feed the base in a reactive way. This database is fed by the services of the Region to fill in the specific territorial devices. You must be identified to query the API (web service) in JSON format of the database https://data.aides-entreprises.fr/api You can find all the support devices available on the regional portal of companies: https://entreprises.maregionsud.fr

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.

The Canadian Business Patterns contains data that reflects counts of business locations (as of December 2008) and business establishments (prior to December 2009) by: 9 employment size ranges, including "indeterminate" (as of December 1997); geography groupings: province/territory, census division, census subdivision (before December 2008), census metropolitan area and census agglomeration; and industry using the North American Industry Classification System (tables at the 2, 3, 4 and 6-digit level) as of December 1998. Before December 2004, these data were also presented using the Standard Industrial Classification (tables at the 1, 2, 3 and 4-digit level). The data published in the Canadian Business Patterns represents the current number of locations or establishments for a specific reference period which is taken from the Business Register Central Frame Data Base. It is not intended for use as a time series because changes that affect the continuity of the data might resu lt from changes in methodology. Some examples are: the change to another version of the Standard Geographical Classification (SGC) or the North American Industry Classification System (NAICS), the addition of the new territory of Nunavut and new rules to better identify inactive units.