Top Feature Stores for Machine Learning data scientists must know in 2022
Introduction
A feature store is a system for managing data that gives data scientists and engineers a central place to find and use data for machine learning. A feature store enables data / (features) to be shared across different machine learning pipelines, which can speed up the development of new models and improve model performance. Feature stores have recently emerged as an important component of the enterprise machine learning stack and is a key component in enabling:
- Automated feature computation
- Share and re-use features across different teams and projects
- Managing feature metadata
- Serve or extract features offline, real-time or on-demand
- Monitor the full lifecycle of features from generation to serving
The two main types of data in machine learning are:
- Batch Data — In most cases, the data originates from data lakes or data warehouses. These are large hunks of data that have been saved for the purpose of being used by models; however, they are not necessarily kept up to current in real time. Example: Data from customers of a bank, such as age, country, etc.
- Real-time Data — Usually these come via…
