Questions: A cybersecurity team for a credit card company is devoted to detecting and preventing cyber attacks on customer data. Their new goal is to send an email notification to a security engineer as soon as a potential attack is detected. The security engineer will determine if a customer needs to be notified. The team is trying out a new tool the company hasn't used before. They are using the tool to "ingest" data for an unsupervised learning model to identify patterns and determine if the patterns are legitimate or fraudulent. In which step of the data science methodology is the team working?

The team is working in the "Modeling" step of the data science methodology.

Explanation:

1. Understanding the Problem: This step involves defining the problem and understanding the requirements. The team has already defined their goal, which is to detect potential cyber attacks.

2. Data Collection and Preparation: This involves gathering and preparing data for analysis. The team is using a new tool to "ingest" data, which suggests they have already collected and are preparing the data for analysis.

3. Modeling: This step involves applying statistical or machine learning models to the data to identify patterns or make predictions. The team is using an unsupervised learning model to identify patterns in the data, which is a key activity in the modeling phase.

4. Evaluation: This step involves assessing the model's performance and determining its effectiveness. The team is not yet evaluating the model, as they are focused on identifying patterns.

5. Deployment: This involves implementing the model in a production environment. The team is not at this stage yet, as they are still working on identifying patterns.

In summary, the team is in the "Modeling" step, as they are using an unsupervised learning model to identify patterns in the data.