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Trulioo Interview Questions and Answers
Ques:- What are the common status codes in HTTP responses
Right Answer:
The common status codes in HTTP responses are:

- **200**: OK
- **201**: Created
- **204**: No Content
- **400**: Bad Request
- **401**: Unauthorized
- **403**: Forbidden
- **404**: Not Found
- **500**: Internal Server Error
- **502**: Bad Gateway
- **503**: Service Unavailable
Ques:- What is OAuth and how does it work in API authentication
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.
Ques:- What is rate limiting in APIs and how is it implemented
Right Answer:
Rate limiting in APIs is a technique used to control the number of requests a user can make to an API within a specific time period. It is implemented by setting thresholds (e.g., requests per minute) and using mechanisms like tokens, counters, or IP address tracking to monitor and restrict access when the limit is exceeded.
Ques:- What are Webhooks and how do they differ from APIs
Right Answer:
Webhooks are user-defined HTTP callbacks that are triggered by specific events in a web application, allowing real-time data transfer. They differ from APIs in that APIs require a request to be made to receive data, while webhooks automatically send data when an event occurs without needing a request.
Ques:- What is the difference between synchronous and asynchronous API calls
Right Answer:
Synchronous API calls wait for the response before moving on to the next task, while asynchronous API calls allow the program to continue executing other tasks while waiting for the response.
Ques:- WHAT IS WORKING CAPITAL
Right Answer:
Working capital is the difference between a company's current assets and current liabilities, indicating the short-term financial health and operational efficiency of the business.
Ques:- Explain in brief about the Documentation – CFD, DFD, Functional Documentation.
Right Answer:
**CFD (Context Flow Diagram)**: A high-level diagram that shows the flow of information between external entities and the system, helping to define system boundaries and interactions.

**DFD (Data Flow Diagram)**: A visual representation that illustrates how data moves through a system, detailing processes, data stores, and data flows, typically used to analyze and design systems.

**Functional Documentation**: A comprehensive document that outlines the functionalities of a system, including requirements, use cases, and specifications, serving as a guide for development and testing.
Ques:- In order to attract deposits, banks offer various types of products with distinguishing features. As a student of banking law do you observe any challenge/threat from money laundering for banks in this struggle? Discuss
Right Answer:
Yes, banks face significant challenges from money laundering when attracting deposits. Money laundering can lead to reputational damage, regulatory penalties, and financial losses. Banks must implement strict compliance measures and due diligence processes to detect and prevent illicit activities, which can complicate their efforts to attract legitimate deposits.
Ques:- How to depict dependency in Ms Project?
Right Answer:
To depict dependency in MS Project, you can link tasks by selecting the tasks you want to connect, then clicking on the "Link Tasks" button in the toolbar or using the shortcut Ctrl + F2. This creates a finish-to-start dependency by default. You can also adjust the type of dependency (finish-to-start, start-to-start, finish-to-finish, or start-to-finish) by double-clicking on the task and modifying the "Predecessors" tab.
Ques:- Tell me about your self and about skills and knowledge
Right Answer:
I am [Your Name], and I have a background in [Your Field/Industry]. I have developed skills in [Key Skills Relevant to the Job, e.g., project management, software development, data analysis], and I am knowledgeable in [Relevant Technologies or Concepts]. I am passionate about [Your Interests Related to the Job] and continuously seek to improve my skills through [Learning Methods, e.g., courses, workshops, hands-on experience].
Ques:- What we should expect from you?
Right Answer:
You can expect me to bring strong communication skills, a collaborative attitude, a commitment to continuous learning, and a proactive approach to problem-solving. I will strive to contribute positively to the team and deliver high-quality work.
Ques:- What is exploratory data analysis (EDA)
Right Answer:
Exploratory Data Analysis (EDA) is the process of analyzing and summarizing datasets to understand their main characteristics, often using visual methods. It helps identify patterns, trends, and anomalies in the data before applying formal modeling techniques.
Ques:- What is data analysis and why is it important
Right Answer:
Data analysis is the process of inspecting, cleaning, and modeling data to discover useful information, draw conclusions, and support decision-making. It is important because it helps organizations make informed decisions, identify trends, improve efficiency, and solve problems based on data-driven insights.
Ques:- How do you handle missing data in a dataset
Right Answer:
To handle missing data in a dataset, you can use the following methods:

1. **Remove Rows/Columns**: Delete rows or columns with missing values if they are not significant.
2. **Imputation**: Fill in missing values using techniques like mean, median, mode, or more advanced methods like KNN or regression.
3. **Flagging**: Create a new column to indicate missing values for analysis.
4. **Predictive Modeling**: Use algorithms to predict and fill in missing values based on other data.
5. **Leave as Is**: In some cases, you may choose to leave missing values if they are meaningful for analysis.
Ques:- What is the purpose of feature engineering in data analysis
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.
Ques:- What is data normalization and why is it important
Right Answer:
Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves structuring the data into tables and defining relationships between them. Normalization is important because it helps eliminate duplicate data, ensures data consistency, and makes it easier to maintain and update the database.
Ques:- Waht is second normal form
Right Answer:
Second Normal Form (2NF) is a database normalization level where a table is in First Normal Form (1NF) and all non-key attributes are fully functionally dependent on the entire primary key, meaning there are no partial dependencies on a composite primary key.
Ques:- Difference between DWH and Data mart, Difference between views and materialized views. What is Indexing and which kind of Indexing Technique we use in
Right Answer:
**Difference between DWH and Data Mart:**
- A Data Warehouse (DWH) is a centralized repository that stores large volumes of data from multiple sources for analysis and reporting. A Data Mart is a subset of a Data Warehouse, focused on a specific business area or department.

**Difference between Views and Materialized Views:**
- A View is a virtual table that provides a way to present data from one or more tables without storing it physically. A Materialized View, on the other hand, stores the result of a query physically, allowing for faster access at the cost of needing to refresh the data periodically.

**Indexing:**
- Indexing is a database optimization technique that improves the speed of data retrieval operations on a database table. Common indexing techniques include B-tree indexing, hash indexing, and bitmap indexing.
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