{"id":26059,"date":"2022-10-13T16:48:28","date_gmt":"2022-10-13T11:18:28","guid":{"rendered":"https:\/\/blog.aspiresys.com\/?p=26059"},"modified":"2025-04-30T06:29:46","modified_gmt":"2025-04-30T06:29:46","slug":"how-to-transform-enrich-data-in-oracle-analytics-cloud","status":"publish","type":"post","link":"https:\/\/www.aspiresys.com\/blog\/oracle\/analytics\/how-to-transform-enrich-data-in-oracle-analytics-cloud\/","title":{"rendered":"How to Transform and Enrich Data in Oracle Analytics Cloud?"},"content":{"rendered":"\n

Oracle Analytics Cloud <\/strong>is a powerful tool that can help you make sense of large amounts of data. With its easy-to-use interface, you can quickly and easily view, analyze, and transform data. One of the best things about Oracle Analytics Cloud is that it’s constantly being updated with new features and enhancements. So, you can still benefit from using it even if you’re not a data analyst. If you’re ready to get started, read on for our guide to transforming and enriching data in Oracle Analytics Cloud<\/strong>. <\/p>\n\n\n\n

Suppose you want to successfully transform and enrich data in Oracle Analytics Cloud (OAC)<\/strong><\/a>. In that case, these are a few key steps: First, it is essential to understand the data and how it is currently stored. Once this is understood, the data can be properly formatted for OAC. Finally, your data must be enriched with the appropriate context to provide the most insights. <\/p>\n\n\n\n

Understand the data <\/strong><\/p>\n\n\n\n

The\nfirst step to properly transforming and enriching data in OAC is understanding\nthe data, including where it comes from, what it represents, and how it is\ncurrently stored. With this understanding, the data can be appropriately\nformatted for OAC. <\/p>\n\n\n\n

Format the data <\/strong><\/p>\n\n\n\n

Once\nthe data is understood, it can be formatted for OAC by ensuring that the data\nis in the correct format and structure for OAC. Additionally, any necessary\ndata cleansing should be performed at this stage. <\/p>\n\n\n\n

Enrich the data <\/strong><\/p>\n\n\n\n

The\nfinal step is to enrich the data with the appropriate context, including\nrelevant metadata, such as geographical data, to the data set. It will help OAC\nto provide more insights and make better recommendations.<\/p>\n\n\n\n

Data transformation through an OAC interface<\/strong><\/h2>\n\n\n\n

The Data Transformation interface in Oracle Analytics Cloud (OAC)<\/strong> is a web-based interface that lets you quickly and easily transform data from various sources into the format required for OAC. The interface provides a drag-and-drop option for mapping source data to OAC data fields and also supports SQL and JavaScript for more complex data transformation. The Data Transformation interface is a vital part of the OAC platform and enables you to quickly and easily load data into OAC for analysis.<\/p>\n\n\n\n

You\ncan easily convert data from one format to another, change data types, and even\nmerge multiple data sources into a single data set. Select the data source you\nwish to transform, and then select the transformation you want to perform. You\ncan specify the transformation details, such as the data type and the target\ndata set. Once you have determined the transformation, click the “Apply”\nbutton, and the transformation will be applied to your data. <\/p>\n\n\n\n

If you need to transform multiple data sources, you can use the “Batch Transformation” feature to quickly and easily transform all of your data sources simultaneously. To use this feature, select the data sources you wish to transform and select the “Batch Transformation” option. You can also specify the transformation you want to perform, and the transformation will be applied to all of your selected data sources. Data Transformation in Oracle Analytics Cloud<\/strong> can save you time and effort when transforming your data. <\/p>\n\n\n\n

Read Also: Oracle Analytics Cloud (OAC): Your Questions, Answered!<\/strong><\/a> <\/p>\n\n\n\n

Steps to transform data in OAC<\/strong><\/h3>\n\n\n\n

The\ndata transformation interface is divided into two sections: the left panel is\nwhere you select the source and target tables, and the right panel is where you\nspecify the transformation rules.<\/p>\n\n\n\n

To\nbegin, select the source and target tables. The source table is the table that\ncontains the data that you want to transform. The target table is the table\nthat will hold the transformed data. In our example, we will use a customer\ntable and an order table.<\/p>\n\n\n\n

Next,\nspecify the transformation rules. There are three transformation rules: column\nmapping, value mapping, and SQL transformation. <\/p>\n\n\n\n