A data product is an app or tool that leverages data to help businesses make better decisions and improve processes. It provides a user-friendly interface while using data and data science methods, so even non-technical users can interact meaningfully with data.
Data products can be used internally within an organization to make data-driven decisions, or be consumer-facing to give customers a level of interaction with your data.
What are some examples of data products?
Data products can take many forms, but they are often used to provide insights, predictions, or recommendations based on data analysis. Some common examples include:
- Predictive models: Predictive models and machine learning algorithms can predict outcomes based on input data. For example, a user of a data product might be able to enter inputs to predict the likelihood that a customer will churn, or to predict the probability that a loan applicant will default on their loan.
- Recommendation engines: Data products can use algorithms to suggest items or content to a user based on their previous behavior. For example, streaming sites like Netflix can use a recommendation engine to suggest new shows or movies to watch.
- Data visualization tools: Data products can help users understand and explore data by creating visual representations of the data. For example, a data visualization tool might be used to create interactive charts, graphs, or maps to help users see trends or patterns in the data.