Dataset Activation with Data Distiller in Adobe Experience Platform
In today's data-driven world, efficiently activating datasets is crucial for maximizing business value. Whether it's AI/ML model training, enterprise reporting, or providing a 360-degree view of your customer, Data Distiller in Adobe Experience Platform (AEP) plays a pivotal role in transforming raw data into structured, actionable insights.
Data Distiller allows you to convert raw datasets into derived datasets that are pre-processed, enriched, and ready for immediate use. This process reduces complexity and significantly enhances the performance of data analysis and model training. By structuring data into a star schema, which includes both fact tables (like sales, revenue) and lookup tables (such as customer demographics), businesses can seamlessly leverage pre-aggregated, optimized data for real-time insights.
Key Benefits of Data Distiller:
Sometimes, exporting datasets in a custom batch audience format may be necessary. Data Distiller supports these special export needs by acting as a contract between AEP and external destinations, ensuring that datasets are structured according to the requirements of the target platform.
Prototyping with Data Landing Zone Destination
In the tutorial below, the Data Landing Zone Destination was used as the central component for prototyping the export of datasets. It served as a staging area where data could be verified before final export, allowing us to quickly check and confirm the content of exported datasets. This streamlined the process of prototyping by providing a reliable method for external systems to access and validate the data.
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Azure Storage Explorer was crucial in understanding the exported data, as it enabled us to browse, view, and download the exported files.
Understanding Data Usage Labeling and Enforcement
In the tutorial, Data Distiller allowed for the application of contract labels such as the C2 label to individual fields within a dataset. The C2 contract label ensures that certain fields cannot be exported to third-party destinations. This mechanism is particularly useful when dealing with datasets that contain sensitive or regulated information. DULE provided the framework to enforce these policies, preventing unauthorized or non-compliant exports, thereby maintaining data integrity and meeting privacy obligations.
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Principal Solutions Architect - Lead at Amazon Web Services (AWS) - Generative AI and Business Applications Technology Strategy | Cloud Evangelist | 13x AWS Certified | 2x SAP Certified |1X GEN AI Certified
3moInsightful as always Saurabh.
Sr Partner , Solutions at IBM Global Systems Inc.
3moDataset activation simplified. Data governance ensured. Saurabh Mahapatra
Mridul Jammalamadaka ! Great information captured in details on Data Distillers! Great to follow and have a working session