Find Interview Questions for Jouve

Right Answer:
The Scrum Master is a servant-leader who helps the Scrum Team follow the Scrum framework. They facilitate Scrum events (Sprint Planning, Daily Scrum, Sprint Review, Sprint Retrospective), remove impediments, protect the team from distractions, and coach the team on Agile principles and practices.

Right Answer:
Scrum is an Agile framework for managing and completing complex projects.

Implementation involves:

1. **Roles:** Defining roles like Product Owner, Scrum Master, and Development Team.
2. **Sprints:** Working in short, time-boxed iterations (Sprints), typically 2-4 weeks.
3. **Artifacts:** Using artifacts like Product Backlog, Sprint Backlog, and Increment.
4. **Events:** Conducting events such as Sprint Planning, Daily Scrum, Sprint Review, and Sprint Retrospective.
5. **Continuous Improvement:** Regularly inspecting and adapting the process based on feedback.

Right Answer:
I've used tools like Jira, Azure DevOps, and Trello for Agile project management. I choose them based on project needs; Jira for complex workflows and robust reporting, Azure DevOps for integrated development environments, and Trello for simpler, visually-oriented task management.

Right Answer:
Cross-functional teams in Agile are important because they bring together all the necessary skills to complete work without dependencies on other teams. This leads to faster delivery, better problem-solving, and increased innovation. To foster collaboration, encourage open communication, shared understanding of goals, mutual respect, and a focus on collective ownership.

Right Answer:
To facilitate effective sprint retrospectives, I would:

1. **Set the Stage:** Create a safe and open environment where the team feels comfortable sharing.
2. **Gather Data:** Collect information about what went well, what didn't, and any challenges faced during the sprint.
3. **Generate Insights:** Facilitate a discussion to identify root causes and patterns.
4. **Decide on Actions:** Collaborate to define specific, actionable, measurable, achievable, relevant, and time-bound (SMART) improvements.
5. **Close the Retrospective:** Summarize action items and assign owners.
6. **Follow Up:** Track progress on action items in subsequent sprints to ensure continuous improvement.

Right Answer:
HTTP methods are standardized request types used in APIs to perform actions on resources. The main methods are:

1. **GET**: Retrieve data from a server.
2. **POST**: Send data to a server to create a new resource.
3. **PUT**: Update an existing resource on the server.
4. **DELETE**: Remove a resource from the server.
5. **PATCH**: Apply partial modifications to a resource.

These methods define the action to be performed on the specified resource in the API.

Right Answer:
OAuth is an open standard for access delegation commonly used for token-based authentication and authorization. It allows third-party applications to access a user's resources without sharing their credentials.

In API authentication, OAuth works by having the user authorize the application to access their data. The process involves:

1. The user is redirected to an authorization server to log in and grant permission.
2. The authorization server issues an access token to the application.
3. The application uses this access token to make API requests on behalf of the user.
4. The API validates the token and grants access to the requested resources.

Right Answer:
An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate with each other. It defines the methods and data formats that applications can use to request and exchange information. APIs work by sending requests from one application to another, which then processes the request and sends back a response.

Right Answer:
An API endpoint is a specific URL or URI where an API can be accessed by a client to perform operations like retrieving or sending data. It defines the location and method (such as GET, POST) for interacting with the API.

Right Answer:
RESTful principles include:

1. **Statelessness**: Each API call must contain all the information needed to understand and process the request, with no stored context on the server.
2. **Client-Server Architecture**: The client and server are separate, allowing for independent development and scalability.
3. **Uniform Interface**: A consistent way to interact with resources, typically using standard HTTP methods (GET, POST, PUT, DELETE).
4. **Resource-Based**: APIs should expose resources (data entities) through URIs, and clients interact with these resources.
5. **Representation**: Resources can be represented in various formats (like JSON or XML), and clients can request the format they prefer.
6. **Cacheability**: Responses should indicate whether they can be cached to improve performance and reduce server load.

These principles guide the design of APIs to be scalable, efficient, and easy to use.

Right Answer:
Outliers are data points that significantly differ from the rest of the dataset. They can skew results and affect statistical analyses. To handle outliers, you can:

1. Identify them using methods like the IQR (Interquartile Range) or Z-scores.
2. Remove them if they are errors or irrelevant.
3. Transform them using techniques like log transformation.
4. Use robust statistical methods that are less affected by outliers.
5. Analyze them separately if they provide valuable insights.

Right Answer:
The purpose of feature engineering in data analysis is to create, modify, or select variables (features) that improve the performance of machine learning models by making the data more relevant and informative for the analysis.

Right Answer:
Descriptive statistics summarize and describe the main features of a dataset, using measures like mean, median, mode, and standard deviation. Inferential statistics use sample data to make predictions or inferences about a larger population, often employing techniques like hypothesis testing and confidence intervals.

Right Answer:
Classification analysis is a data analysis technique used to categorize data into predefined classes or groups. It works by using algorithms to learn from a training dataset, where the outcomes are known, and then applying this learned model to classify new, unseen data based on its features. Common algorithms include decision trees, logistic regression, and support vector machines.

Right Answer:
Clustering in data analysis is the process of grouping similar data points together based on their characteristics, without prior labels. It is an unsupervised learning technique. In contrast, classification involves assigning predefined labels to data points based on their features, using a supervised learning approach.