The primary difference between Code-First and Database-First approaches in Entity Framework lies in how the database schema and application's data model are created. In Code-First, developers define the application's data model using classes, and the database schema is then generated based on these classes. In contrast, Database-First starts with an existing database schema, from which Entity Framework generates the application's data model as classes. This fundamental distinction affects the development workflow and the way developers interact with the database during application development.

ADO.NET Entity Framework abstracts the database schema, allowing developers to interact with conceptual entities rather than dealing directly with database tables and columns. This abstraction simplifies data access and makes the application more maintainable and adaptable to changes in the underlying database structure.

In the Code-First approach of Entity Framework, to update data, you retrieve the entity from the database, modify its properties, and then call the SaveChanges() method on the context to persist the changes to the database. The framework handles tracking changes and generating the necessary SQL statements to update the database.

The DataView class in ADO.NET is commonly employed for advanced data binding tasks. It allows for flexible sorting, filtering, and searching of data within a DataTable, making it suitable for various data presentation needs.

When using a DataAdapter to fill a DataSet, the commonly used SQL statement is SELECT. This statement is used to retrieve data from a database based on specified criteria. It allows you to fetch data from one or more tables, apply filters, and define the order of results. By executing a SELECT statement, the DataAdapter retrieves the requested data and fills it into the DataSet for further manipulation and analysis within the application.

The main difference between IEnumerable and IQueryable in LINQ lies in their execution behavior. IEnumerable is suitable for querying in-memory collections where execution happens on the client side. IQueryable, on the other hand, is used for querying databases where execution occurs on the server side. IQueryable allows for composing LINQ queries and executing them remotely, while IEnumerable supports deferred execution but lacks this remote execution capability.

The SqlConnection class in ADO.NET is responsible for managing the connection pool. It provides methods for opening, closing, and managing connections to a SQL Server database. When connection pooling is enabled, SqlConnection automatically manages the pooling of database connections, optimizing the performance of database interactions in .NET applications.

DataAdapters are database-agnostic, meaning they can work with various database providers without requiring changes to the application code. This flexibility allows developers to switch between different database systems such as SQL Server, Oracle, and SQLite seamlessly, simply by changing connection strings or configurations.

Proper error handling in ADO.NET transactions often involves using try-catch blocks to handle exceptions. A try-catch block allows developers to handle exceptions gracefully by catching and handling errors that may occur during transaction processing, ensuring robustness and reliability in application behavior.

Advanced data binding in ADO.NET often requires using data transformers to manipulate data before displaying it. These transformers can perform operations like formatting, filtering, or aggregating data to suit the presentation requirements.

LINQ queries can be written in both query syntax and method syntax. Method syntax involves using extension methods and lambda expressions, making "Method" the correct option for the second blank.

The significance of the DataAdapter's FillSchema method is that it defines the schema of the dataset based on the schema of the data source. This allows for the creation of a dataset with the appropriate structure to accommodate the data retrieved from the data source. It is particularly useful when the dataset needs to be populated with data from a data source whose schema may change over time.