Hello there,
Firstly, the responses to your questions below
1. Database and data warehouse are both fundamentally meant for storing data but data warehouse is a layer on top of a regular database to enable fast and complex Analytics and operations on the data available in a database. Database is in itself is not ideal to run complex analytics across multiple systems but suitable to capture transactional data mostly, like retail transactions at a store but to produce advanced analytics and reports using that data, it will be ideal to create an OLAP layer which will enable
faster retrieval and processing of data.
2. Precision and recall are commonly used to evaluate the performance of classification models.
Precision is basically what fraction of the data points classified under a particular category are actually correct. Other way to say this is that it is ratio of true positives to total positives predicted by the model.
Recall is what fraction of the datapoints belonging to a certain category was the model able to detect correctly, in other words ratio of predicted true positives to the total positives that actually exist in the data.
I am a data science consultant with more than 8.5 years of experience working full time with clients across the globe in data driven decision making. I have trained more than 1200 busines leaders and specialized in bridging the gap between data and business teams.
Hoping to work with you!
Best,
Yash