Tracks: Data 360

Data Cloud Overview

Identify typical use cases for Data Cloud.

Articulate how Data Cloud works and its dependencies.

Describe and apply the principles of data ethics.

Data Cloud Setup and Administration

Apply Data Cloud permissions, permission sets, and org-wide settings.

Describe and configure the available data stream types and data bundles.

Identify use cases for data spaces and create data spaces based on requirements.

Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits.

Diagnose and explore data using Data Explorer, Profile Explorer, and APIs.

Data Ingestion and Modeling

Identify the different transformation capabilities within Data Cloud.

Describe processes and considerations for data ingestion from different sources into Data Cloud.

Define, map, and model data using best practices and aligning to requirements for identity resolution.

Use available tools to inspect and validate ingested and modeled data.

Identity Resolution

Describe matching and how its rule sets are applied.

Reconcile data and describe how its rule sets are applied.

Describe the results of identify resolution and use cases.

Segmentation and Insights

Define basic concepts of segmentation and use cases.

Identify scenarios for analyzing segment membership.

Configure, refine, and maintain segments within Data Cloud.

Identify and differentiate between calculated and streaming insights.

Act on Data

Define activations and their basic use cases.

Use attributes and related attributes.

Identify and analyze timing dependencies affecting the Data Cloud lifecycle.

Troubleshoot common problems with activations including accepted/rejected counts, errors, and not seeing related attributes.

Use data actions and identify their requirements and intended use cases.