Workday Prism Analytics Training provides trainees with a full picture of their business by empowering analysts to enrich their analytics in Workday with data from any source. Students would learn how to create data pipelines that blend and transform the data using Prism functions. Prism data source can be secured using the configurable security framework so that it can be published for use in Workday reports. Trainees would also be taught how to perform ad hoc analysis in data discovery. It is essential to opt for Workday HCM Training before learning Prism Analytics.
The objectives of Workday Prism Analytics Training include learning the creation of data pipelines , blending and transforming data by adding stages and configuring Prism calculated fields, configuring Prism data source security and publish for consumption in Workday reports and learning how to list strategies for managing Prism data.
Data management is an essential part of prism analytics training in Workday. Prism Analytics Data Management Workflow consists of analyzing Workday and non-Workday data together without having to export it into a separate data warehouse and BI (business intelligence) application. This makes analysis faster, easier, more secure, and performed in a location where users can take action. To create a dataset from a Workday report, the report must be an advanced report, be enabled as a web service, be enabled for Prism Analytics and should not include any fields from a related business object that have a many to 1 relationship with the primary business object.
Prism Data Sources
A Prism data source is a type of Workday data source that gets created when a dataset is published. A dataset is a user-defined object in the Prism Analytics Data Catalog that describes transformed data. Workday creates a Prism data source and loads it with the transformed data as configured in the dataset. Typically, datasets blend together Workday and non-Workday data.
Table and Dataset Concepts
A table is a Workday Prism Analytics object that stores (materializes) data and represents it in a tabular format. A table has a user-defined schema and only contains data that's valid against the schema. The data in tables is backed by a distributed columnar data store. A dataset is a description of the data, otherwise known as metadata. Trainees can create datasets to prepare data for analysis. Each table and dataset field has a field type attribute. The field type is often referred to as a data type in other data applications.
Securing Data in Tables and Datasets
Prism Analytics uses a strong, flexible, and configurable security model to control access to data, objects, and tasks. Trainees would learn how to have fine-grained control over what they can do with tables and datasets. Sharing tables and datasets is a way to control access to individual tables and datasets.
Deleting Prism Analytics Data
When students delete rows in a Prism data source, the Prism data source is empty and becomes inactive. The dataset can be edited to correct the transformation logic and publish the dataset again. When the dataset is republished again, Workday populates the empty, inactive Prism data source with the new data.
Data discovery is a tool that enables analysts to create visual analytics from Workday Prism Analytics data sources and display them using discovery boards. The environment is intended for ad hoc analysis and exploration of Prism Analytics data sources. The discovery board is the canvas for discovering and sharing data insights. Students would learn this concept in-depth during the course of the training.Type something