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Mysql create view specify column type8/17/2023 ![]() ![]() If you do not create a column like ad_source, there is no easy way to identify spend from a particular source. Remember that this query combines all data from both tables. A new column called ad_source is created to make it easier to filter for AdWords or Facebook data.The order in which columns are called in the SELECT queries dictates how they are lined up. For the sake of clarity, all columns are aliased above such that the names match across all queries.Usually, consolidating your Facebook and Google AdWords spend data into a Data Warehouse View require the creation of a table with seven columns, with a query similar to the below: SELECTĪ couple of important points about the above: When executing a UNION or UNION ALL statement, the names of the columns in the final output reflect the naming of columns in your first query. Corresponding columns must have identical data types.All queries must return the same number of columns.There are a few requirements of a UNION statement worth mentioning, as outlined in the PostgreSQL documentation: A UNION ALL statement is most often used to combine multiple distinct SQL queries while appending the results of each query to a single output. To create a single ad spend table containing both Facebook and Google AdWords campaigns, you must write a SQL query and use the UNION ALL function. Most commonly this involves the consolidation of two tables, with sample data sets below: Look a closer look at one of the examples mentioned earlier in this article: consolidating Facebook and AdWords spend data into a new consolidated ads table. Example: Facebook and Google AdWords data Because Data Warehouse Views are not editable, Adobe recommends that you test the output of your query using the SQL Report Builder before saving your query as a Data Warehouse View. When migration is complete, you can safely delete the original view. If you need to adjust the structure of a Data Warehouse View, you must create a view and manually migrate any calculated columns, metrics, or reports from the original view to the new one. It is important to mention that after saving, the underlying query used to generate a Data Warehouse View cannot be edited. After being processed by an update, your view is ready to use in reports. Your view temporarily has a Pending status until it is processed by the next full update cycle, at which point the status changes to Active. When you are finished, Click Save to save your view. ![]() The use of the *character to select all columns is not permitted. Your query must reference specific column names. ![]() ![]() All other characters are forbidden.Įnter your query in the window titled Select Query, using standard PostgreSQL syntax. View names are limited to lower case letters, numbers, and underscores (_). The name provided here determines the display name for the view in the Data Warehouse. Give the view a name by typing in the View Name field. If a blank query window is already open, proceed to the next step. If observing an existing view, click New Data Warehouse View to open a blank query window. New Data Warehouse Views can be created and existing views can be deleted by navigating to Manage Data > Data Warehouse Views, as shown below:įrom here you can create a view by following the sample instructions below: Creating and Managing Data Warehouse Views If you are familiar with SQL, both of these consolidation examples use the UNION function, but you can use any PostgreSQL syntax and functions when building a new view. A few common examples include consolidating the tables from a legacy database and a live database to combine historical and current data, or combining multiple ad sources like Facebook and AdWords into a singular Consolidated ad spend table. Once a Data Warehouse View has been created and processed by an update cycle, it populates in your Data Warehouse as a new table under the Data Warehouse Views dropdown, as shown below:įrom here, your new view functions like any other table, giving you the power to create new calculated columns or build metrics and reports on top of it.ĭata Warehouse Views are primarily used to consolidate multiple similar but disparate tables together, such that all reporting can be built on a single new table. The Data Warehouse Views feature is a method of creating new warehoused tables by modifying an existing table, or joining or consolidating multiple tables together by using SQL. Below is an explanation of what it does and how to create views, as well as an example of how to use Data Warehouse Views to consolidate Facebook and AdWords spend data. This document outlines the purpose and uses of Data Warehouse Views accessible by navigating to Manage Data > Data Warehouse Views. ![]()
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