Adobe Analytics - Data Workbench Architect training course covers a detailed synopsis of the product architecture, instruction on data acquisition, and the configuration of various components of the Data Workbench platform to process and prepare data for analysis and reporting purposes. This Program discusses the creation and configuration of dimensions to extend the Data Workbench dataset, while also presenting the key stages of data processing, profile creation and configuration, log source definition, specialized transformations for manipulating and cleansing data, conditions, and the use of data transformation and integration engines.
Adobe Analytics - Data Workbench Architect ACE training course provides in-depth training for candidates who want to configure and construct datasets to support their clients’ business analysis needs. The skills gained in this course enable architects to determine an appropriate implementation strategy and successfully satisfy business requirements.
- Describe the different data acquisition methods
- Understand the fundamentals of log data processing
- Build and manage a custom profile
- Know the conditions and transformations available for manipulating data
- Extend the dataset schema with new reporting dimensions
- Administer communication between Client and Server
- Understand advantages/disadvantages of various data acquisition methods
- Understand the data process flow
- Build and manage custom profiles
- Practice using conditions and transformations to present the most meaningful data to business users
- Extend the dataset schema with new reporting dimensions
- Identify and correct errors in configuration through troubleshooting exercises
Adobe Analytics - Data Workbench Architect ACE
- Attending a training on Data Workbench Analyst, OR
- Successful completion of the Data Workbench Analyst certification exam
Adobe Analytics - Data Workbench Architect class is specifically designed for personnel who function as the Data Workbench technical lead-the individual within the organization who is responsible for translating client’s business requirements into specific Data Workbench transformations and dimensions by making dataset design and configuration decisions.