Corporate Profits in the United States increased to 3259.41 USD Billion in the second quarter of 2025 from 3252.44 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

About Dataset

Context

Analytics refers to the methodical examination and calculation of data or statistics. Its purpose is to uncover, interpret, and convey meaningful patterns found within the data. Additionally, analytics involves utilizing these data patterns to make informed decisions. It proves valuable in domains abundant with recorded information, employing a combination of statistics, computer programming, and operations research to measure performance.

Businesses can leverage analytics to describe, predict, and enhance their overall performance. Various branches of analytics encompass predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, Big Data Analytics, retail analytics, supply chain analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, graph analytics, credit risk analysis, and fraud analytics. Due to the extensive computational requirements involved (particularly with big data), analytics algorithms and software utilize state-of-the-art methods from computer science, statistics, and mathematics.

Data Dictionary

Content

This Dataset consists of salaries for Data Scientists, Machine Learning Engineers, Data Analysts, and Data Engineers in various cities across India (2022).

-Salary Dataset.csv -Partially Cleaned Salary Dataset.csv

Acknowledgements

This Dataset is created from https://www.glassdoor.co.in/. If you want to learn more, you can visit the Website.

Analysis of ‘FAANG- Complete Stock Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/aayushmishra1512/faang-complete-stock-data on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

There are a few companies that are considered to be revolutionary. These companies also happen to be a dream place to work at for many many people across the world. These companies include - Facebook,Amazon,Apple,Netflix and Google also known as FAANG! These companies make ton of money and they help others too by giving them a chance to invest in the companies via stocks and shares. This data wass made targeting these stock prices.

Content

The data contains information such as opening price of a stock, closing price, how much of these stocks were sold and many more things. There are 5 different CSV files in the data for each company.

--- Original source retains full ownership of the source dataset ---

Xverum’s Alternative Data delivers a unique lens into the evolving landscape of global businesses - offering non-traditional insights built from social media signals and public web profiles. With over 750M enriched professional profiles and 50M verified companies, this dataset empowers investors, hedge funds, and analysts to identify hidden trends, benchmark headcount dynamics, and make smarter portfolio decisions.

Our data bridges the gap between surface-level company metrics and internal workforce dynamics - ideal for those seeking high-signal, low-noise intelligence.

🔍 Key Features: ✅ Social Media–Derived Insights: Profiles collected and enriched from open social platforms and web sources. ✅ Workforce Trend Monitoring: Track hiring surges, downsizing, department shifts, and growth by role or region. ✅ Educational Intelligence: Understand degree types, universities, and certifications across a company’s talent base. ✅ 50M Company Profiles: Enriched with org size, industry, location, and growth signals. ✅ Dynamic Dataset: Monthly refresh with 350M+ updates per month to ensure timeliness. ✅ Fully GDPR/CCPA-Compliant: Ethically sourced and privacy-secure.

Primary Use Cases: 💠 VC & Hedge Fund Due Diligence Spot early-stage momentum and pre-IPO growth by tracking hiring trends, talent density, and team structure shifts.

💠 Investment Signal Generation Discover investment opportunities based on headcount expansion, leadership changes, and team expertise indicators.

💠 Corporate Intelligence & Benchmarking Compare peer companies by workforce size, education level, technical background, and hiring speed.

💠 Talent Strategy & Workforce Analytics Analyze top roles, degrees, and backgrounds across competitive organizations.

Why Xverum’s Alternative Data? ✅ 750M Verified Professional Profiles ✅ 50M Company Datasets with rich firmographics ✅ Unique social-driven signals for workforce tracking ✅ Investor-grade alternative intelligence ✅ Bulk delivery in .json or .csv formats ✅ S3 Bucket, Email, Cloud Services - fully flexible delivery

Request a free sample today and discover how our social media–powered alternative data can enhance your investment strategies, VC scouting, and workforce due diligence.

Green credit is changing industrial structure and corporate behavior, but little attention has been paid to the relationship between green credit and corporate cash management behavior. Based on the typical fact that the allocation of traditional bank credit funds is biased towards heavily polluting industries and the exogenous impact event of green credit policy, this paper takes A-share listed companies in China’s capital market from 2008 to 2015 as samples, and uses the DID model to investigate the impact of green credit policy on excess cash holdings of heavily polluting enterprises. The findings indicate that the green credit policy has reduced the excessive cash holdings of heavily polluting enterprises, suggesting that it can correct the issue and align their cash holdings with the requirements of normal production and operations. The mechanism test demonstrates that the green credit policy can alleviate agency conflicts and influence enterprise cash holdings. Moreover, a cross-sectional investigation reveals that the inhibitory effect of the green credit policy on cash holdings is more pronounced in large-scale and state-owned enterprises compared to small-scale and non-state-owned enterprises. Finally, an analysis of the economic consequences reveals that the green credit policy indirectly enhances corporate value by reducing excessive cash holdings. Based on this, banks and financial institutions continue to treat the credit granting of heavily polluting enterprises cautiously, optimize the structure of green financial products, fully consider the different types and nature of customers, and develop differentiated lending conditions and diversified evaluation mechanisms. This paper has enriched the research on the economic consequences of green credit and the influencing factors of corporate cash holdings, and provided policy enlightenment for regulators and listed companies to correctly understand and make full use of green credit policies to keep corporate cash stable through the crisis.

The Corona crisis (COVID-19) affects a large proportion of companies and freelancers in Germany. Against this background, the study examines the personal situation and working conditions of employees in Germany in times of corona. The analysis mainly refers to the situation in May 2020 and can only make limited statements about the further situation of the employed persons in the course of the corona pandemic. Personal situation: change in working times during the corona crisis; current work situation (local focus of one´s own work); preference for home office; preference for future home office; financial losses due to the corona crisis; concerns about the financial and economic consequences of the corona crisis in Germany; concerns about the corona crisis in personal areas (job security, current working conditions, financial situation, career opportunities, family situation, health, psychological well-being, housing situation); support from the employer in the corona crisis. 2. Economy and welfare state: political interest; assessment of the economic situation in Germany; preferred form of government (strong vs. liberal state); agreement on various statements on the weighing of values in the Corona crisis (the restrictions on public life to protect the population from Corona are not in proportion to the economic crisis caused by it, the money now being made available for economic aid will later be lacking in other important areas such as education, infrastructure or climate protection, for politicians, the health of the population is the top priority, the interests of the economy influence them less strongly with regard to the corona crisis, the worst part of the crisis is now behind us, as a result of the economic effects of the corona crisis the contrast between rich and poor in Germany will become even more pronounced, the corona crisis affects the low earners more than the middle class, the corona crisis significantly advances the digitalisation of the world of work); perception of state action in the corona crisis on the basis of pairs of opposites (e.g. bureaucratic - unbureaucratic, passive - active, etc.); responsibility of the state to provide financial support to companies in the corona crisis; responsibility of the state to provide financial support to private individuals in the corona crisis over and above basic provision; recipients of state financial aid in the corona crisis (companies, directly to needy private individuals, companies and private individuals alike); assessment of the bureaucracy involved in state financial aid (speed vs. exact examination). 3. Measures: awareness of current measures to support business and individuals in the corona crisis; assessment of current measures to support business and individuals in the corona crisis; reliance on assistance in the corona crisis; nature of assistance used in the corona crisis; barriers to use of assistance in the corona crisis; assessment of the effectiveness of the state measures to cope with the corona crisis; appropriate additional measures to mitigate the economic consequences; concerns about the consequences of the planned state measures (increasing tax burden, rising social contributions, rising inflation, stagnating pension levels, rising retirement age, reduction of other state transfers, safeguarding savings). 4. Information: active search for information on financial assistance offers by the Federal Government in the corona crisis; self-assessment of the level of information on measures to support business and private individuals in the corona crisis; request for detailed information on state assistance measures in the corona crisis (e.g. application process, sources of funding, conditions for receiving assistance, etc.) sources of information used about state aid measures in the Corona crisis; contact with institutions offering economic and financial aid during the Corona crisis (development bank/ municipal development agency, employment agency, tax office, none of them); experience with institutions offering economic and financial aid during the Corona crisis (appropriate treatment). 5. Outlook: assessment of the future economic situation in Germany; assessment of Germany´s future as a strong business location; assessment of its own future economic situation; assessment of the duration of the economic impairment caused by the Corona crisis. Demography: age; sex; education; employment; self-localization social class; net household income; current household income; household income before the crisis; occupational activity; belonging to systemically important occupations; number of persons in the household; number of children under 18 in the household; size of town; party sympathy; migration background. Additionally coded: current number; federal state; education (low, medium, high); weighting factor.

Context

There are a few companies that are considered to be revolutionary. These companies also happen to be a dream place to work at for many many people across the world. These companies include - Facebook,Amazon,Apple,Netflix and Google also known as FAANG! These companies make ton of money and they help others too by giving them a chance to invest in the companies via stocks and shares. This data wass made targeting these stock prices.

Content

The data contains information such as opening price of a stock, closing price, how much of these stocks were sold and many more things. There are 5 different CSV files in the data for each company.

Tourism Revenues in the United States decreased to 20626 USD Million in July from 20913 USD Million in June of 2025. This dataset provides - United States Tourism Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2023, Meta Platforms had a total annual revenue of over 134 billion U.S. dollars, up from 116 billion in 2022. LinkedIn reported its highest annual revenue to date, generating over 15 billion USD, whilst Snapchat reported an annual revenue of 4.6 billion USD.

Oracle’s cloud services and license support division is the company’s most profitable business segment, bringing in over ** billion U.S. dollars in its 2025 fiscal year. In that year, Oracle brought in annual revenue of close to ** billion U.S. dollars, its highest revenue figure to date. Oracle Corporation Oracle was founded by Larry Ellison in 1977 as a tech company primarily focused on relational databases. Today, Oracle ranks among the largest companies in the world in terms of market value and serves as the world’s most popular database management system provider. Oracle’s success is not only reflected in its booming sales figures, but also in its growing number of employees: between fiscal year 2008 and 2021, Oracle’s total employee number has grown substantially, increasing from around ****** to *******. Database market The global database market reached a size of ** billion U.S. dollars in 2020. Database Management Systems (DBMSs) provide a platform through which developers can organize, update, and control large databases, with products like Oracle, MySQL, and Microsoft SQL Server being the most widely used in the market.

How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

In 2024, Google ranked as the most valuable media and entertainment brand worldwide, with a brand value of 683 billion U.S. dollars. Facebook ranked second, valued at around 167 billion dollars. Part of the Tencent Group, WeChat and v.qq.com (Tencent Video) had a brand value of 56 billion and 17.5 billion dollars, respectively.

Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.

Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.

During a 2024 survey, 77 percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just 23 percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis.

              Social media: trust and consumption

              Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than 35 percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than 50 percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media.

              What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis.
              Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers.
              Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.