Adobe Customer Journey Analytics Developer Expert key terms

A container in Customer Journey Analytics that holds imported event, profile, lookup, or summary data plus its schema and settings. It connects to a source such as Experience Platform or an uploaded file.

The configuration that links one or more Adobe Experience Platform datasets into Customer Journey Analytics and defines which data is available for analysis, including dataset-level settings like person ID and data source type.

A container layered on top of a connection that defines how data is interpreted for reporting: component settings, attribution, session rules, and filters. Multiple data views can share one connection.

A reusable reporting element in a data view, such as a dimension, metric, or segment, that is built from schema fields and configured with settings like visibility, naming, and formatting.

The field in a dataset that identifies an individual, used as the basis for identity stitching and cross-device analysis. Choosing a stable, high-coverage identifier is critical for accurate person-level reporting.

The process of reconciling multiple identifiers (such as ECID and CRM ID) into a single person so events from different devices or sources are attributed to one individual during analysis.

A named identity type in Adobe Experience Platform, such as ECID, email, or CRM ID, that labels an identifier so stitching and identity graphs can interpret and link values correctly.

Reporting that combines events from multiple sources or touchpoints, such as web and call center, into one view by resolving identities and aligning data through shared dimensions and timestamps.

An identity stitching method that uses a persistent field in the data, such as a CRM or loyalty ID, to group events into a person. It requires that the field be present and consistent across datasets.

An identity stitching method that relies on the Adobe Experience Platform identity graph, which links namespaces across datasets to resolve a person. It depends on identity service configuration.

A data view setting that determines how credit for a metric is distributed across dimension values over a lookback window, such as last touch, first touch, or linear.

The time range a data view uses to search backward for dimension values when attributing a metric, such as allocating a purchase to a marketing channel seen in the prior 30 days.

A quantitative component in a data view, such as events, orders, or revenue, that is calculated from schema fields and configured with settings like format, visibility, and attribution behavior.

A metric built from a formula that combines existing metrics using arithmetic, functions, or filters. It is created in the component interface and can be shared across projects.

A reusable set of conditions that includes or excludes data, such as events, sessions, or persons, so that analysis focuses on a subset. Filters are components built in a data view.

The scope setting on a filter that determines what the conditions apply to: person-level across all data, session-level within a visit, or event-level for individual hits.

A grouping of events attributed to one person within a defined period of inactivity. Data view session settings control timeout length and what starts a new session.

The inactivity interval that ends a session in a data view. Events after the timeout start a new session, affecting metrics like visits and session-scoped filters.

A formal definition of the structure of a dataset, including field names, data types, and relationships. Customer Journey Analytics reads data according to the schema exposed by the source.

Experience Data Model, Adobe's standard schema for structuring experience data. Datasets ingested through Experience Platform typically conform to an XDM schema with classes and field groups.

A dataset setting in Customer Journey Analytics that declares whether the dataset contains event, profile, lookup, or summary data, which determines how it is joined and used in reporting.

A dataset used to enrich event data by joining additional attributes on a matching key, such as mapping a product ID to a product name. It is configured with a key and lookup fields.

A dataset containing pre-aggregated data, such as daily totals, that can be combined with event data in a data view. It supports reporting where granular event records are unavailable.

Tags applied to datasets or fields that describe sensitivity and contractual restrictions, such as identity or export limits. They drive policy enforcement in Customer Journey Analytics.

A rule in Adobe Experience Platform that restricts how labeled data may be used, such as preventing use of sensitive data for certain purposes. Violations surface during analysis or export.

A record of user actions and system events, such as changes to connections, data views, or exports, used to investigate incidents and demonstrate compliance.

A person's permission for data collection or use, often stored as a field in the data. Reporting can be filtered by consent values to respect opt-in and opt-out choices.

The set of practices and controls that protect personal data, including consent handling, data minimization, deletion requests, and governance labels that limit how identifiers are used.

A field created in a data view from existing schema fields using rules or functions, such as extracting a page section from a URL. It behaves like a dimension in reporting.

A saved analysis in Analysis Workspace containing panels, visualizations, and components. Projects can be shared and scheduled and are the primary vehicle for delivering insights.

A Workspace visualization that displays dimensions as rows and metrics as columns, supporting breakdowns, sorting, and filtering. It is the most common starting point for exploratory analysis.

The action of splitting a dimension or metric value into its component values within a visualization, revealing the underlying detail behind an aggregate number.

A categorical component used to group or describe data, such as page name, channel, or device type. Dimensions are built from schema fields and configured in a data view.

The process of correcting or reprocessing data after an ingestion or configuration problem, such as re-importing a dataset or adjusting settings so historical data is interpreted correctly.

Diagnosing reporting discrepancies by checking data ingestion status, identity stitching coverage, data view settings, attribution, and filter logic to locate the source of unexpected results.

The process of bringing source data into Customer Journey Analytics, whether through Experience Platform datasets, streaming sources, or file uploads, so it becomes available for analysis.

Loading historical data into a dataset or connection so past periods can be analyzed. Backfills are often needed when adding a new source or correcting gaps in existing data.

A chart or table in Analysis Workspace, such as a line chart, bar chart, or flow diagram, that presents data from a panel in a visual form for interpretation.