MetaData

Microsift Stock Price Data (2010-2024)

Dataset Description

This dataset contains historical stock price data for Microsoft from 2010 to 2024. This data is extracted by using Python's yfinance library and it provides detailed insights into Microsoft stock performance over the years. It includes daily values for the stock's opening and closing prices, adjusted close price, high and low prices, and trading volume. This dataset is ideal for time series analysis, stock trend analysis, and financial machine learning projects such as price prediction models and volatility analysis.

The dataset is extracted from Yahoo Finance

Column Descriptions

Date: The trading date for each entry, in the format.

Adj_Close: Adjusted closing price of Microsoft stock for each trading day, reflecting stock splits, dividends, and other adjustments.

Close: The raw closing price of Microsoft stock at the end of each trading day.

High: The highest price reached by Microsoft stock during the trading day.

Low: The lowest price reached by Microsoft stock during the trading day.

Open: The price of Microsoft stock at the start of the trading day.

Volume: The total number of shares traded during the trading day.

📁 Dataset 3: Microsoft Corp. (MSFT)

💻 Microsoft Corp. (MSFT) Stock Price Data – Last 5 Years

Description:
This dataset contains daily historical stock price data for Microsoft Corporation (Ticker: MSFT) over the past 5 years. It is sourced from reliable financial market data providers and is well-suited for:

• 📈 Time series forecasting and trend analysis
• 📊 Financial dashboards and visualizations
• 🧠 Machine learning applications in finance
• 💼 Investment research and strategy backtesting

Each entry corresponds to a single trading day and includes various price indicators and trading volume.

Columns Included:

• Date: The calendar date of the trading session (YYYY-MM-DD).
• Open: The price of the stock at the beginning of the trading day.
• High: The highest price reached during the trading day.
• Low: The lowest price recorded during the trading day.
• Close: The price of the stock at the end of the trading session.
• Adj Close: The closing price adjusted for splits and dividend distributions.
• Volume: The total number of shares traded during that day.

🔍 Beginner-Friendly Analysis Techniques:

If you're new to data analysis or finance, here are some simple but powerful techniques you can apply:

• Line Plots: Use line charts to visualize how the stock price has changed over time.
• Moving Averages: Calculate simple or exponential moving averages to identify trends and smooth out short-term fluctuations.
• Daily Returns: Compute percentage change between closing prices to analyze daily gains or losses.
• Volatility Analysis: Use rolling standard deviation to understand how volatile the stock has been.
• Volume Trends: Track trading volume to identify periods of high market activity.
• Candlestick Charts (intermediate): Create candlestick charts to represent daily open-high-low-close patterns visually.

Use Cases:
This dataset can be used to evaluate stock performance trends, calculate technical indicators, simulate investment strategies, or train predictive models on financial data.

Microsoft reported $24.04B in Cost of Sales for its fiscal quarter ending in September of 2025. Data for Microsoft | MSFT - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Microsoft reported $1.13B in Stock for its fiscal quarter ending in September of 2025. Data for Microsoft | MSFT - Stock including historical, tables and charts were last updated by Trading Economics this last December in 2025.

The Data Exchange Platform Services market is experiencing robust growth, driven by the increasing need for secure and efficient data sharing across organizations. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The rise of cloud computing and the increasing adoption of APIs are simplifying data exchange processes and reducing costs, making data exchange platforms more accessible to businesses of all sizes. Furthermore, stringent data privacy regulations, such as GDPR and CCPA, are driving the demand for secure and compliant data exchange solutions. The growing importance of data analytics and the need for real-time data insights across different systems also contribute significantly to market growth. Major players like Amazon Web Services, Microsoft, and IBM are actively investing in and expanding their data exchange platform offerings, further fueling market competition and innovation. The market is segmented by deployment (cloud, on-premises), organization size (small, medium, large), and industry vertical (healthcare, finance, retail, etc.). The cloud deployment segment is expected to dominate due to its scalability, flexibility, and cost-effectiveness. The increasing adoption of data exchange platforms in the healthcare and finance sectors, driven by the need for secure patient data sharing and financial transactions, is also significantly contributing to market growth. However, challenges remain, including concerns over data security and integration complexities, which can act as restraints to market expansion. Overcoming these challenges through robust security protocols and user-friendly interfaces will be crucial for sustained market growth. The competitive landscape is characterized by the presence of established technology giants and specialized data exchange platform providers. This intense competition fosters innovation and drives down prices, ultimately benefiting end-users.

AZURE Minerals reported 1.33M in Cost of Sales for its fiscal semester ending in December of 2023. Data for AZURE Minerals | AZS - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Discover the explosive growth of the shared bandwidth package market, projected to reach $45 billion by 2033. This in-depth analysis reveals key drivers, trends, and challenges, examining major players like AWS, Microsoft Azure, and Alibaba Cloud, along with regional market shares and future forecasts. Learn how cost-effective and scalable internet connectivity is shaping the future of business and technology.

Discover the booming Data Sharing Cluster market analysis, revealing a CAGR-driven expansion fueled by cloud computing, data privacy regulations, and AI. Learn about key players like AWS, Azure, and IBM, and explore regional market trends shaping this dynamic sector through 2033.

The booming Business Cloud Storage and File Sharing market is projected to reach $150 billion by 2033, driven by remote work, cybersecurity concerns, and collaborative needs. Explore market trends, key players (like Microsoft, Dropbox, Google), and regional growth in this comprehensive analysis.

The data marketplace market is experiencing robust growth, driven by the increasing demand for data-driven decision-making across various industries. The market, estimated at $15 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a compound annual growth rate (CAGR) of approximately 20%. Several key factors contribute to this expansion. The rising volume of data generated by businesses and the need for efficient data monetization are key drivers. Furthermore, the increasing adoption of cloud computing and advanced analytics platforms provides a robust infrastructure for data marketplaces to thrive. The emergence of new data privacy regulations, while posing certain restraints, also simultaneously create opportunities for secure and compliant data exchange platforms. The market is segmented by data type (structured, unstructured), industry vertical (healthcare, finance, retail), and deployment model (cloud, on-premise). Key players like Amazon, Microsoft, and others are actively shaping the market landscape through technological innovation and strategic partnerships. Competition is intensifying, with companies focusing on developing innovative solutions to cater to specific industry needs and enhance data security. The long-term outlook for the data marketplace market remains positive, with continued growth anticipated through 2033. However, challenges persist. Interoperability issues between different data platforms and ensuring data quality remain significant hurdles. The need for robust data governance and security frameworks is critical to building trust and encouraging wider adoption. Future market growth will depend on addressing these challenges effectively, fostering industry collaboration, and developing standardized protocols for data exchange and sharing. Addressing concerns around data privacy and ethical considerations will also be paramount to sustainable growth. The evolving regulatory landscape necessitates continuous adaptation and innovation to ensure compliance and responsible data handling practices.

Background:

Companies' worth or its total market value is called market capitalization or market cap. It is equal to the share price multiplied by the number of shares outstanding. Stock price is a proportional and relative value of companies' growth. Here, analyzing the stock price data will help us to understand a company's growth. An increase in stock price increases the company's market value.

Objective:

We have Collected the latest data of Microsoft Stock price and calculated daily log return which is approximately normally distributed. Let us try to answer some of the questions that will help us to decide roughly whether to invest in the Microsoft shares or not?

a) What is the probability that the stock price will drop over 5% in a day?

b) What is the probability that the stock price will drop over 10% in a day?

c) What is the probability that the stock price will drop over 50% in a year?

d) What is the probability that the stock price will drop over 25% in a year?

e) What is the 50th percentile of the yearly stock price?

Dataset:

MSFT.csv: It contains information about the stock price of Microsoft.

Date: Date of the stock price

Open: The average value of opened price on a particular day

Close: The average value of closed price on a particular day

Low: The lowest price reached on a particular day

High: The highest price reached on a particular day

Discover the booming Key-Value Database market! Our analysis reveals a $1288.8 million market in 2025, projecting robust growth driven by cloud adoption and big data. Learn about key players (AWS, Azure, etc.), market trends, and regional insights. Explore the future of NoSQL and high-performance data storage.

The online file-sharing platform market is experiencing robust growth, driven by the increasing adoption of cloud computing, remote work trends, and the need for seamless collaboration across geographically dispersed teams. The market, estimated at $50 billion in 2025, is projected to experience a Compound Annual Growth Rate (CAGR) of 15% throughout the forecast period (2025-2033). This growth is fueled by the rising demand for secure and efficient data storage and sharing solutions across various industries, including healthcare, education, and finance. Key drivers include enhanced security features, improved accessibility via mobile devices, and the integration of advanced functionalities such as version control and real-time collaboration tools. The market is segmented by platform type (consumer vs. enterprise), deployment model (cloud vs. on-premises), and pricing model (freemium vs. subscription), each presenting unique opportunities for growth. Competitive pressures remain intense, with established players like Microsoft, Google, and Dropbox competing alongside emerging providers offering specialized solutions. The competitive landscape is characterized by a mix of large, established players offering comprehensive suites of productivity and collaboration tools and smaller, niche players focusing on specific market segments or functionalities. The market's evolution is marked by a steady shift towards cloud-based solutions, driven by scalability, cost-effectiveness, and enhanced accessibility. Potential restraints include data security and privacy concerns, regulatory compliance issues, and the integration complexity for legacy systems. However, ongoing technological advancements and increased awareness of the benefits of cloud-based file sharing are expected to mitigate these challenges. The market is expected to witness further consolidation as smaller players are acquired by larger companies, leading to a more concentrated market in the long term. The forecast period of 2025-2033 will likely see significant innovation in areas like AI-powered file management and enhanced security protocols.

AZURE Minerals reported 1.69B in Market Capitalization this May of 2024, considering the latest stock price and the number of outstanding shares.Data for AZURE Minerals | AZS - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December in 2025.

The Big Data Integration Platform market is poised for significant expansion, projected to reach approximately USD 1802 million in 2025. Fueled by a robust Compound Annual Growth Rate (CAGR) of 10.7%, this dynamic sector is expected to witness substantial value appreciation throughout the forecast period ending in 2033. This growth is primarily driven by the escalating volume and complexity of data generated across industries, necessitating sophisticated solutions for seamless data ingestion, transformation, and management. The increasing adoption of cloud-based integration platforms, offering scalability, flexibility, and cost-effectiveness, is a pivotal trend. Furthermore, the growing demand for real-time data processing and analytics to gain competitive advantages is propelling market momentum. Large enterprises, with their extensive data ecosystems, and Small and Medium-sized Enterprises (SMEs) alike are investing in these platforms to unlock valuable insights from their data assets. While the market benefits from strong growth drivers, certain restraints could influence its trajectory. The complexity of integrating diverse data sources and legacy systems can pose technical challenges and increase implementation costs for some organizations. Moreover, concerns surrounding data security and privacy, particularly with sensitive information, require robust platform capabilities and adherence to stringent regulations. However, the continuous innovation in data integration technologies, including AI-powered automation and enhanced data governance features, is expected to mitigate these challenges. Key players like IBM, SnapLogic, Azure Data Factory (ADF), and Talend are actively developing advanced solutions to address these evolving market needs, ensuring the Big Data Integration Platform market continues its upward trajectory. This report provides an in-depth analysis of the global Big Data Integration Platform market, encompassing a comprehensive study of its dynamics, trends, and future trajectory. The Study Period spans from 2019 to 2033, with the Base Year and Estimated Year set at 2025. The Forecast Period extends from 2025 to 2033, building upon the insights gathered during the Historical Period of 2019-2024. We have meticulously examined key players like IBM, SnapLogic, Azure Data Factory (ADF), Apache NiFi, Talend, Information Builders, Data Virtuality, Apache Sqoop, Denodo, Apache Gobblin, HVR, and Oracle, and segmented the market across Applications (Large Enterprises, SMEs), Types (Cloud Based, Web Based), and Industry Developments. Our analysis projects a market valuation exceeding $100 million by the end of the forecast period, with substantial growth driven by increasing data volumes and the need for unified data management.

The cloud storage software market is experiencing robust growth, driven by the increasing need for secure and scalable data storage solutions across various sectors. The market's expansion is fueled by several key factors: the escalating volume of data generated by businesses and individuals, the rising adoption of cloud computing technologies for improved efficiency and cost-effectiveness, and the growing demand for enhanced data security and disaster recovery capabilities. Organizations across BFSI, government, healthcare, and other sectors are migrating their data to the cloud to leverage advantages like pay-as-you-go models, reduced IT infrastructure costs, and improved accessibility. The market is segmented by deployment type (private, public, hybrid) and application, with the hybrid cloud model gaining traction due to its ability to combine the benefits of both private and public clouds. While data privacy concerns and security breaches pose challenges, the market is expected to overcome these through robust security measures and compliance with evolving data protection regulations. The competitive landscape is characterized by a mix of established players like Amazon Web Services, Microsoft, and Google, alongside specialized providers focusing on specific industry needs. Based on a projected CAGR (assume a conservative 15% based on industry averages), and a 2025 market size of $100 billion (a reasonable estimate given the scale of cloud computing), we can anticipate substantial market expansion throughout the forecast period (2025-2033). The geographic distribution of the market reveals a concentration in North America and Europe, reflecting high cloud adoption rates and robust digital infrastructure in these regions. However, Asia-Pacific is expected to witness significant growth, driven by increasing digitalization in developing economies like India and China. The competitive intensity is likely to remain high, with companies focusing on innovation, strategic partnerships, and mergers and acquisitions to gain market share. Future growth will likely be driven by advancements in technologies like AI-powered data management, edge computing, and the increasing adoption of serverless architectures. Overall, the cloud storage software market presents significant opportunities for both established and emerging players, with continued growth expected across various segments and regions throughout the forecast period.

This dataset contains the predicted prices of the asset Microsoft Tokenized Stock (Ondo) over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains the predicted prices of the asset Microsoft tokenized stock (xStock) over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

In the second half of 2022, all user data requests issued to Microsoft by law enforcement agencies in the Dominican Republic resulted in the disclosure of only subscriber or transactional data, excluding content data. In the Lithuania, over 90 requests ended up with partial disclosure.

Dataset Description This dataset contains historical stock price data across multiple timeframes, ranging from intraday to higher timeframes. The available timeframes include:

1-minute (1m) 5-minute (5m) 30-minute (30m) 60-minute (1h) 240-minute (4h) Daily (1D) Weekly (1W) Monthly (1M)

Each dataset file represents price movements at a specific timeframe, enabling traders and analysts to perform technical analysis across different granularities.

Columns - datetime: The timestamp or date of the recorded price data. - open: The opening price at the beginning of the timeframe. - high: The highest price reached within the timeframe. - low: The lowest price reached within the timeframe. - close: The closing price at the end of the timeframe. - % change: The percentage change in price from the previous timeframe, indicating the rate of price movement.

Exchange Information The dataset is sourced from the IC Market exchange, ensuring reliable and up-to-date market data. https://in.tradingview.com/broker/ICmarkets/

Time Period Covered The dataset spans from the inception of the company to 2025, covering complete historical stock price data.

Potential Use Cases - Technical analysis: Identifying trends, support/resistance levels, and chart patterns. - Algorithmic trading: Backtesting strategies across multiple timeframes. - Machine learning models: Training predictive models for stock price movements. - Volatility analysis: Understanding market behavior across different timeframes.