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Some basic steps are required in order to be able to access and manipulate data using ADO : Create a connection object to connect to the database. Create a recordset object in order to receive data in. Open the connection; Populate the recordset by opening it and passing the desired table name or SQL statement as a parameter to open function.
ADO.NET is a data access technology from the Microsoft.NET Framework that provides communication between relational and non-relational systems through a common set of components. [1] ADO.NET is a set of computer software components that programmers can use to access data and data services from a database.
In ADO.NET, a DataReader is a broad category of objects used to sequentially read data from a data source. [1] DataReaders provide a very efficient way to access data, and can be thought of as a Firehose cursor from ASP Classic, except that no server-side cursor is used.
Data adapters are an integral part of ADO.NET managed providers, which are the set of objects used to communicate between a data source and a dataset. (In addition to adapters, managed providers include connection objects, data reader objects, and command objects.) Adapters are used to exchange data between a data source and a dataset.
A recordset is a data structure that consists of a group of database records, and can either come from a base table or as the result of a query to the table. The concept is common to a number of platforms, notably Microsoft's Data Access Objects (DAO) and ActiveX Data Objects (ADO). The Recordset object contains a Fields collection, and a ...
In software, a data access object (DAO) is a pattern that provides an abstract interface to some type of database or other persistence mechanism. By mapping application calls to the persistence layer, the DAO provides data operations without exposing database details. This isolation supports the single responsibility principle.
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Also confidence coefficient. A number indicating the probability that the confidence interval (range) captures the true population mean. For example, a confidence interval with a 95% confidence level has a 95% chance of capturing the population mean. Technically, this means that, if the experiment were repeated many times, 95% of the CIs computed at this level would contain the true population ...