Data quality and quantity

Define good data to begin the process. A model is only as good as the data that it is provided.

When the business problem is defined explicitly, map out the right data for your model. Data is a vital part of every machine learning model. To build an accurate and efficient model, you must feed it a huge volume of data. Models need to be trained on large data to learn good generalizations.

Ask these questions:

Is the data relevant to the business case?
Can a sufficient quantity of data be supplied?