Microsoft Technology Licensing, LLC

Jeffrey Michael Derstadt

Arthur John Cerdic Vickers

Andrew Peters

Diego Bernardo Vega

Rowan Laurence Miller

Michael Pizzo

Timothy A Laverty

Colin Joseph Meek

Daniel Galen Simmons

Brian C Dawson

Nadejda V Poliakova

Sarah M Parra

Ravinder R Vuppula

James Madison Stone, Iii

Patrick T Magee

Shyamalan Pather

Andrew Conrad

Carl Yates Perry

Amanda K Silver

Paul Allen Vick, Jr

David E Sceppa

Jeffrey E Reed

Arthur John Cedric Vickers

Identifying data quality along a data flow. A method includes identifying quality metadata for two or more datasets. The quality metadata defines one or more of quality of a data source, accuracy of a dataset, completeness of a dataset, freshness of a dataset, or relevance of a dataset. At least some of the metadata is based on results of operations along a data flow. Based on the metadata, the method includes creating one or more quality indexes for the datasets. The one or more quality indexes include a characterization of quality of two or more datasets.

Using lineage to infer data quality issues

Techniques are described herein that are capable of translating programming language patterns into database schema patterns. Examples of a programming language pattern include but are not limited to a source code pattern, an intermediate language code pattern, metadata associated with a source code pattern, metadata associated with an intermediate language code pattern, or any combination thereof. The programming language patterns may define objects that are included in an object model. Database schema patterns that define a database are automatically (e.g., inferentially) created based on respective programming language patterns that define objects of an object model. The programming language patterns are automatically mapped to the respective database schema patterns.

Translating metadata associated with code patterns into database schema patterns

A method is directed to associating quality metadata with underlying data. The method includes, for one or more data items, a computing system identifying one or more threshold conditions related to the data items. The computing system determines that the one or more threshold conditions related to the data items have been met. As a result of determining that the one or more threshold conditions related to the data items have been met, the computing system associates quality metadata with the data items.

Event-triggered data quality verification

Translating programming language patterns into database schema patterns

Systems and methods that enable relationship information to be carried along with data objects when serializing/deserializing data objects among application tiers. A tracking component tracks information on relationships associated with a data object, and further enables subsequent change processing on the data object's relationship information. Accordingly, relationship information can be carried along with the data object, such that database operation can be performed without requirement of additional information from the database (e.g., foreign key information that is part of associated graphs).

Relationship serialization and reconstruction for entities

Systems and methods that enable relationship information to be carried along with the entity when serializing/deserializing entities among application tiers. A tracking component tracks information on relationships associated with an entity, and further enables users to perform subsequent change processing on the entity's relationship information. Accordingly, relationship information can be carried along with the entity such that database operation can be performed without requirement of additional information from the database (e.g., foreign key information that is part of associated graphs).

Fluent API Patterns promote balance in managing object persistence. Code which obtains an object-relational mapper session contains API Patterns that manipulate persistence ignorant objects using calls to a fluent interface. When the developer's code executes, it may manipulate an object state, a property state, and/or a persistent relationship of the persistence ignorant object. The code may implement API Patterns such as find-change-save, current-value-original-value, nested-property, incremental-graph-load, incremental-graph-filtered-load, property-modification, dictionary, and/or other API Patterns. Additional examples of API Patterns include an API Pattern to read current, original, and database values for all properties of an entity; an API Pattern to set current and/or original values from another object; and an API Pattern to create a cloned object containing current, original, and/or database values. In any or all of these situations, the API Pattern calls to the fluent interface may be written in a strongly typed language.

Fluent API patterns for managing object persistence

Aspects of the subject matter described herein relate to mapping from application objects to an abstract data model. In aspects, a mapper receives registrations that indicate behavior (e.g., how objects are constructed, modified, or examined) of application objects. The behavior may be specified using user-supplied expressions. The mapper aggregates this data and uses it to map application requests for data access into one or more operations that operate on the abstract data model. A data access layer may then translate the operations into actions to access data corresponding to the requests from a store. If appropriate, data obtained from the store may then be inserted into application objects as indicated by the registrations.

Mapping from objects to data model

There is alteration of a late-bound expression produced by a compiler into an early-bound structure. Alteration of the late-bound expression can occur at runtime and a visitor pattern can be used to create the alteration. In one instance, a conversion from late-bound to early-bound takes place through replacing a late-bound property with a statically typed call. The early-bound structure can translate into an expression tree to enable an implementation of a store specific query operated upon storage.

Translating late bound LINQ expressions into database queries

Programmers typically like operating with databases through use of classes. Classes allow a user to function with a database through use of a non-database programming language. To ease use of the classes, a class context is generated at runtime that does not force a programmer to handle various source files that are a product of class generation. Therefore, the user can have the ease of using classes without having to perform extra actions.

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Jeffrey Michael Derstadt