Graph and download economic data for Commercial Banks in the U.S. with average assets under $100M (DISCONTINUED) (US100NUM) from Q1 1984 to Q3 2020 about commercial, assets, banks, depository institutions, and USA.

Brazil Direct Investment: Liabilities: Equity Capital: Inflow: Transactions Between US$100 Million and US$500 Million data was reported at 172.108 USD mn in May 2019. This records a decrease from the previous number of 1.003 USD bn for Apr 2019. Brazil Direct Investment: Liabilities: Equity Capital: Inflow: Transactions Between US$100 Million and US$500 Million data is updated monthly, averaging 1.140 USD bn from Mar 2014 (Median) to May 2019, with 63 observations. The data reached an all-time high of 3.100 USD bn in Nov 2017 and a record low of 150.000 USD mn in Aug 2015. Brazil Direct Investment: Liabilities: Equity Capital: Inflow: Transactions Between US$100 Million and US$500 Million data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Investment – Table BR.OA017: Direct Investment: Liabilities: Equity Capital: Inflow: by Value Ranges.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

MrBeast's $100 Million Fund Aims to Help Creators Change the World

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

ST - DHS Public Access Database: Consistent with the 2013 OSTP Memorandum and the 2022 update, “Increasing Access to the Results of Federally Funded Scientific Research,” directed all agencies with greater than $100 million in R&D expenditures each year to prepare a plan for improving the public’s access to the results of federally funded research, specifically peer-reviewed scholarly publications and digital data. In response to the memorandum, DHS developed a DHS Public Access Plan, and intends to make available to the public digitally formatted scientific data that support the conclusions in peer-reviewed scholarly publications that are the results of DHS R&D funding. This data repository site with a customized DHS Storefront allows DHS to post releasable scientific digital data from peer-reviewed publications resulting from DHS-funded research. The data repository is configured to allow DHS users (and publishers acting on behalf of these users) to deposit data sets into the repository, making them available to the general public.

A major flooding event occurred on January 22, 2024 in San Diego County. The Emergency Operations Center (EOC) was activated January 22, 2024 - June 21, 2024. This data summarizes over 1,250 households or cases managed by Equus (County contractor) and the County in a non-congregate Emergency Temporary Lodging (ETL) Program for households and individuals displaced by the flooding. This data also summarizes the overall financial investment by the County and federal agencies, totaling more than $100 million. This data includes summary information from FEMA's Individuals and Household Program. All previously published reports can be found here: https://www.alertsandiego.org/en-us/recovery/events/jan-21-2024-flood-activation/recovery.html

Data changed rapidly throughout the response as duplicate records were identified and household composition changed.

Data from: County of San Diego FEMA, Major Disaster Number DR-4758-CA Equus Workforce Solutions

The size of the Data Warehouse as a Service Market was valued at USD 57.21 Billion in 2023 and is projected to reach USD 228.82 Billion by 2032, with an expected CAGR of 21.9% during the forecast period. Data Warehouse as a Service (DWaaS) is displaying rapid growth as the market becomes flooded with a significantly increased request for scalable, cost-effective, cloud storage and analytics. Storage and analysis of vast structured and unstructured data by businesses is offered by DWaaS without the need for any kind of on-premise structural background. DWaaS is diversified into a number of applications such as finance, healthcare, retail, and IT. This is because it helps streamline data management and improves business intelligence for fast-in-time decisions. Key drivers for the market include cloud computing adoption at significant speed, an awakening of data-driven strategies, and advancement in big data analytics, and artificial intelligence. The increasing importance of disaster recovery and backup solutions and the need for operational efficiency add to the market's favor. Emerging markets actively involved in investment in IT and more digital transformation would give impetus to the ever-flourishing market. Recent developments include: June 2022: Amazon Web Services has a partnership with HCL Technologies. HCL can provide enterprise data warehousing solutions that are scalable, economical, secure, and high-performing thanks to AWS. HCL Technologies receives data-driven business insights from Amazon Redshift that are supported by cutting-edge AI/ML capabilities to enhance operational effectiveness, decision-making, and accelerate time to market., January 2022: Firebolt’s data warehouse firm secured $100 million at a valuation of USD 1.4 billion to offer speedier, less expensive analytics on enormous data volumes. It planned to use the money to expand its business and hire more skilled employees to better serve the data warehousing industry while also continuing to invest in its technology infrastructure., June 2022: Yellow Brick, a US company located in California, has debuted the most recent iteration of their data warehouse technology. The yellow brick cloud-native elastic data warehouse expands to meet growing business data demands, works both on-premises and in the cloud, and has a clear pricing structure with predictable costs.. Key drivers for this market are: Big Data Analytics Data-Driven Decision Making Operational Efficiency. Potential restraints include: Service Provider Dependency High Costs Integration Challenges. Notable trends are: Growing Expansion of Cloud Computing to boost the market growth.

The African data center cooling market, currently valued at $100 million (estimated based on a 0.1 market size in millions), is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 31.56% from 2025 to 2033. This surge is driven by the increasing adoption of cloud computing, the proliferation of data centers across various sectors (IT & Telecom, Retail, Healthcare, Media & Entertainment, and government agencies), and a rising demand for reliable power and cooling solutions in a region experiencing rapid digital transformation. The market is segmented by cooling technology (air-based, including chillers, CRACs, and other technologies; and liquid-based, encompassing immersion, direct-to-chip, and rear-door heat exchangers), data center type (hyperscalers, enterprise, and colocation), and end-user industry. The preference for cooling technologies will likely shift towards more efficient liquid-based solutions as data center density increases and energy costs remain a significant concern. Growth will be concentrated in key markets like South Africa, Nigeria, and Egypt, reflecting their advanced digital infrastructure and economic development. However, challenges remain, including inconsistent power grids, high capital expenditure requirements, and a need for skilled technicians, potentially hindering market penetration in certain regions. The leading players in the market, including Stulz GmbH, Vertiv, Schneider Electric, and others, are investing heavily in research and development to improve cooling efficiency, reduce energy consumption, and meet the diverse needs of the African data center landscape. The market's expansion will be shaped by government initiatives promoting digital infrastructure development, improving internet penetration, and attracting foreign investment in technology sectors. The ongoing expansion of 5G networks and the increasing adoption of IoT devices will further fuel demand for advanced data center cooling solutions, creating opportunities for both established vendors and emerging players in the coming years. Successful players will need to adapt to the unique challenges of the African market, offering customized solutions that consider factors like climate, power reliability, and local expertise availability. Recent developments include: May 2024: Stulz unveiled its latest innovation, the CyberCool Coolant Management and Distribution Unit (CDU), specifically engineered to optimize heat exchange efficiency in liquid cooling solutions. The product line comprises four models, available in two distinct sizes. These units boast an impressive heat exchange capacity, ranging from 345 kW to 1,380 kW. Stulz set the rated water supply temperature for the facility water system at 32°C (89.6°F), with the liquid supply temperature for the technology cooling system pegged at 36°C (96.8°F).May 2024: Rittal, in collaboration with multiple hyperscale data center operators, developed a modular cooling system. This solution boasts a cooling capacity exceeding 1 MW, achieved through direct water cooling. It is specifically tailored to cater to the high-power densities of AI applications.. Key drivers for this market are: Government initiatives and rising demand for digitalization are propelling market growth., Increasing Cloud based businesses drives the demand for the studied market. Potential restraints include: Government initiatives and rising demand for digitalization are propelling market growth., Increasing Cloud based businesses drives the demand for the studied market. Notable trends are: IT and Telecom Expected to Witness Highest Growth.

The Artificial Intelligence (AI) in Tennis market is rapidly evolving, transforming how athletes, coaches, and organizations approach training, performance analysis, and fan engagement. With an estimated market size of over $100 million in 2023, the integration of AI technologies into the tennis industry has seen a

Access over 825 million global LinkedIn profiles data enriched with detailed B2B LinkedIn people profiles and LinkedIn company data. This LinkedIn dataset offers accurate, structured information for professionals across industries, geographies, and company sizes. It is designed to support sales intelligence, recruiting, marketing, enrichment, investment research, and data platforms.

Our LinkedIn profile dataset includes verified and frequently updated records, making it ideal for data-driven teams looking to scale outreach, identify decision-makers, enrich CRM records, and improve targeting.

LinkedIn profile dataset :

755M+ LinkedIn People Profiles

70M+ LinkedIn Company Profiles

Full Name, Job Title, Company, Industry

LinkedIn Public Identifier and Profile URL

Location, Seniority, Education, Skills

Company Size, Revenue Range, Company Domain, Domain rank

Bi-Weekly Data Updates

Delivery Formats: CSV, JSON, PostgreSQL

API Access with Credit-Based Pricing

Use Cases

Sales Prospecting: Target decision-makers and buyers by title, seniority, region, and industry.

Recruiting: Source passive candidates using skills, experience, education, and seniority filters.

Data Enrichment: Append LinkedIn profile data to your CRM, CDP, or internal database.

Investment Research: Identify executive teams, founders, and key leadership at global companies.

Marketing Automation: Build high-quality outbound and ABM campaign lists using live LinkedIn data.

Technology & SaaS Platforms: Integrate LinkedIn profile data into your product via API.

Key Features

High-accuracy B2B LinkedIn data with 95%+ verified records

Wide global coverage across North America, Europe, LATAM, APAC, and MENA

Fast delivery with bi-weekly refresh cycles

Flexible access via API or flat file delivery

Supports real-time and large-scale enrichment workflows

GDPR and CCPA compliant

Who Uses This Data

Sales Intelligence Tools

Talent Acquisition & HR Tech Platforms

CRM and CDP Vendors

Private Equity and Venture Capital Firms

Data Enrichment Providers

Martech and Adtech Companies

Research and Analytics Firms

Delivery Options

API-based credit system (starting at $100 for 2,500 credits)

One-time file deliveries for specific LinkedIn IDs or data samples

Ongoing flat file subscriptions (CSV, JSON, or PostgreSQL)

Hourly or Bi-weekly refresh options

Trial & Evaluation Sample data and trial API credits are available to validate accuracy and fit for your use case. Volume-based pricing and custom delivery formats can be discussed on request.

Every year since 2020, The Information selects 50 companies that have the potential to be the most valuable businesses in their categories based on their current revenue, business model, and growth prospects. To build the list, our reporters consulted industry sources and gathered previously undisclosed financial information. We limited the list to startups that had raised less than $100 million in funding or began operations within the last two years.

As part of the American Recovery and Reinvestment Act, NYSERDA administered an $18.7 million residential high-efficiency appliance rebate program called New York's Great Appliance Swap Out. Under the approved U.S. Department of Energy plan, customers purchasing appliances qualified for a rebate of $75 ($105 with documented recycling) for ENERGY STAR qualified refrigerators, $75 ($100 with documented recycling) for clothes washers and $50 ($75 with documented recycling) for freezers. $500 rebate ($555 with documented recycling) were also available for high-efficiency dishwashers, clothes washers and refrigerators that meet CEE super efficiency levels when they were purchased as part of a three-appliance package. The plan was approved by the DOE on December 1, 2009. The program was launched February 12, 2010 and closed March 4, 2011 after processing over $16.58 million in rebates.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

These reports contain the name, ABN, total income, taxable income and tax payable for • Australian public and foreign-owned corporate tax entities with a total income of $100 million or more; and • Australian-owned resident private companies with a total income of $200 million or more.

They also contain the name, ABN and tax payable for any entity that has a petroleum resource rent tax (PRRT) payable amount. Entities that had minerals resource rent tax (MRRT) payable were included for the 2013-14 and 2014-15 MRRT years only.

Nigeria Imports of Fertilizers was US$244.74 Million during 2024, according to the United Nations COMTRADE database on international trade. Nigeria Imports of Fertilizers - data, historical chart and statistics - was last updated on July of 2025.