About the webinar:
Metadata management is critical for organizations looking to understand the context, definition and lineage of key data assets. Data models play a key role in metadata management, as many of the key structural and business definitions are stored within the models themselves. Can data models replace traditional metadata solutions? Or should they integrate with larger metadata management tools & initiatives? Join this webinar to discuss opportunities and challenges around:
-How data modeling fits within a larger metadata management landscape
-When can data modeling provide “just enough” metadata management
-Key data modeling artifacts for metadata
-Organization, Roles & Implementation Considerations
About the speaker: Donna Burbank
Donna Burbank, is a recognized industry expert in information management with over 20 years of experience in data management, metadata management, and enterprise architecture. She currently is Managing Director of Global Data Strategy, an international data management consulting company. Her background is multi-faceted across consulting, product development, product management, brand strategy, marketing, and business leadership. Prior to this role, Donna was the Global Practice Director for Information Management at an international consulting company, EAC Group, providing consulting and thought leadership for key clients worldwide. She has served in key brand strategy and product management roles at CA Technologies and Embarcadero Technologies for several of the leading data management products in the market. As an active contributor to the data management community, she is a long time DAMA International member and is the President of the DAMA Rocky Mountain chapter. She was also on the review committee for the Object Management Group’s Information Management Metamodel (IMM) and a member of the OMG’s Finalization Taskforce for the Business Process Modeling Notation (BPMN). She has worked with dozens of Fortune 500 companies worldwide in the Americas, Europe, Asia, and Africa and speaks regularly at industry conferences.
She has co-authored two books: Data Modeling for the Business and Data Modeling Made Simple with CA ERwin Data Modeler r8.
A trigger is a named PL/SQL unit that is stored in the database and executed ( fired ) in response to a specified event that occurs in the database.
Overview of Triggers.
A trigger is a named program unit that is stored in the database and fired (executed) in response to a specified event. The specified event is associated with either a table, a view, a schema, or the database, and it is one of the following:
A database manipulation (DML) statement ( DELETE , INSERT , or UPDATE )
A database definition (DDL) statement ( CREATE , ALTER , or DROP )
A database operation ( SERVERERROR , LOGON , LOGOFF , STARTUP , or SHUTDOWN )
The trigger is said to be defined on the table, view, schema, or database.
A DML trigger is fired by a DML statement, a DDL trigger is fired by a DDL statement, a DELETE trigger is fired by a DELETE statement, and so on.
An INSTEAD OF trigger is a DML trigger that is defined on a view (not a table). The database fires the INSTEAD OF trigger instead of executing the triggering DML statement. For more information, see Modifying Complex Views (INSTEAD OF Triggers).
A system trigger is defined on a schema or the database. A trigger defined on a schema fires for each event associated with the owner of the schema (the current user). A trigger defined on a database fires for each event associated with all users.
A simple trigger can fire at exactly one of the following timing points :
Before the triggering statement executes.
After the triggering statement executes.
Before each row that the triggering statement affects.
After each row that the triggering statement affects.
A compound trigger can fire at more than one timing point. Compound triggers make it easier to program an approach where you want the actions you implement for the various timing points to share common data. For more information, see Compound Triggers.