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A schema crosswalk is a table that shows equivalent elements (or "fields") in more than one database schema.It maps the elements in one schema to the equivalent elements in another.
Design analysis [5] should establish the scalability of an ETL system across the lifetime of its usage – including understanding the volumes of data that must be processed within service level agreements. The time available to extract from source systems may change, which may mean the same amount of data may have to be processed in less time.
Yes - Export SQL No No MySQL Workbench: Yes Yes Yes Yes - CSV, HTML, JSON, MS Excel, SQL INSERTS, Tab-separated, XML: Yes - CSV, HTML, JSON, MS Excel, SQL INSERTS, Tab-separated, XML: Yes No Oracle SQL Developer: Yes Yes Yes Yes Yes Yes Yes Yes pgAdmin: Yes Yes No CSV, Text, or binary CSV, text, HTML, XML: Yes No phpMyAdmin: Yes Some Yes
A staging area, or landing zone, is an intermediate storage area used for data processing during the extract, transform and load (ETL) process. The data staging area sits between the data source(s) and the data target(s), which are often data warehouses, data marts, or other data repositories.
Operational systems maintain a snapshot of the business, while warehouses maintain historic data through ETL processes that periodically migrate data from the operational systems to the warehouse. Online analytical processing (OLAP) is characterized by a low rate of transactions and complex queries that involve aggregations. Response time is an ...
Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format.
Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, [1] and can provide a single customer view (or single view of any other entity) of the overall data.