Discover what a dataset entails, the various types available, and how businesses, AI, and analytics depend on datasets for making decisions and driving innovation.
A dataset is a collection of data organised in a structured format.
It can be a table, a spreadsheet, or a database where information is arranged in rows and columns.
Datasets are used in data analysis, machine learning, and business intelligence to extract insights and support decision-making.
Datasets come in various forms depending on their structure and purpose:
Structured Dataset – Organized in a predefined format, such as a database or Excel sheet.
Unstructured Dataset – Contains information like text, images, and videos without a defined format.
Time-Series Dataset – Data collected over time, commonly used in financial and weather forecasting.
Relational Dataset – Stored in relational databases where data is linked across multiple tables.
Open Dataset – Publicly available datasets for research, such as Kaggle or government databases.
Datasets are the foundation for data science, machine learning, and business intelligence.
Here’s why they matter:
Decision-Making – Businesses use datasets to analyze trends and improve strategies.
Training AI Models – Machine learning algorithms learn from datasets to make accurate predictions.
Scientific Research – Researchers use datasets to validate theories and discover new insights.
Healthcare & Finance – Hospitals and financial institutions rely on datasets for risk assessment and patient management.
Netflix – Uses datasets to recommend movies and TV shows based on viewing history.
Amazon – Analyzes purchase datasets to optimize product recommendations.
Google Maps – Uses geospatial datasets to provide accurate navigation routes.