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Predicting Startup Success Metrics
Data Science and Analytics
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About
The collection of financial records tracks the expenditures and resulting profits of fifty distinct startup entities. It is designed to facilitate financial modelling, regression analysis, and performance benchmarking across key operational spending categories.
Brief Description
This dataset provides detailed operational and financial metrics for 50 startup companies, allowing users to analyse the relationship between various spending categories—namely Research & Development, Administration, and Marketing—and the resulting profit generated. It is an excellent resource for building predictive models focused on understanding the drivers of early-stage business success.
Columns
- Sl. No.: A sequential index number for each startup record.
- R&D Spend: The monetary amount allocated to research and development activities. This category averages around 73.7k.
- Administration: The funds spent on managing administrative tasks and overhead. The mean expenditure is approximately 121k.
- Marketing Spend: The resources dedicated to promotional and marketing campaigns. This field shows a high mean expenditure of 211k.
- State: The geographical location of the startup. The data includes records from three primary locations: New York, California, and other states.
- Profit: The final financial profit achieved by the startup. The average profit recorded is about 112k.
Distribution
The data is provided in a small-sized CSV file, measuring 3.22 kB. The structure consists of 50 unique records and six distinct variables. Crucially for analytical purposes, the dataset is clean, with no missing or mismatched values across any column. The data is expected to receive annual updates.
Usage
- Developing predictive machine learning models to forecast profit based on spending habits.
- Performing regression analysis to quantify the influence of R&D versus Marketing expenditure on profits.
- Benchmarking the financial performance of new ventures against a set of 50 established spending patterns.
- Studying the geographical impact (State) on startup profitability and spending allocation.
Coverage
The data covers operational and financial snapshots for fifty startup companies. Geographically, the records are associated with locations in the United States, predominantly New York and California, which each account for 34% of the records. The scope is entirely focused on financial metrics (expenditure and profit).
License
CC0: Public Domain
Who Can Use It
- Students and Academics: For educational exercises in statistical modelling and business case studies.
- Business Analysts: For quick performance benchmarking and calculating profitability ratios across different expenditure types.
- Machine Learning Engineers: For training and testing linear regression algorithms and evaluating feature importance.
Dataset Name Suggestions
- 50 Startup Expenditure and Profit Data
- Predicting Startup Success Metrics
- Financial Benchmarks for New Companies
- R&D, Marketing, and Administration Spending Analysis
Attributes
Original Data Source: Predicting Startup Success Metrics
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