Extract Transform Load (ETL) Process

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Grand Canyon University *

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408

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Computer Science

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Dec 6, 2023

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Brian Centers SYM – 408 November 18, 2022 Professor Laurence Dean Assignment #4: Extract Transform Load (ETL) Process Each of the SQL Server Integration Services data flow components is classified into one of three categories: sources, destinations, and transformations. Most data flows consist of at least one source and one destination, and optionally contain one or more transformations. Data Flows have different types of connectors that can be used to connect to different types of data sources, depending on which sources you are needing to connect, including Flat File source, Excel source, OLE DB Source, ADO Net Source, XML, and ODBC. There are different types of transformations available in Data Flow Task to use. To perform different logic on your incoming data from source(s), you can use different types of transformation as per your requirements. Derived Column Transformation can be used to add a new column or implement different logics on incoming data. You can write expressions in Derived Column Transformation and make sure of variable and incoming columns. Aggregate Transformation can be used to perform Aggregate functionality on incoming data. Merge Join Transformation is used to join incoming data streams from different sources. Multicast Transformation can divide incoming stream data into multiple outputs. Conditional Split
Transformation divides the data into multiple outputs depending upon incoming data values. Different logics can be written to generate data branches depending upon incoming data values. Union All Transformation merges data coming from multiple data sources. There are varieties of destinations available those can be used to load data into different type of destinations, depending on which program you want to load the data, such as Flat File, Excel, OLÉ DB, Raw File, Excel, ADO NET, SQL Server, and ODBC.
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