Adobe CJA Business Practitioner Pro key terms

The CJA-level link between one or more Experience Platform datasets and the reporting environment. It defines which datasets are joined, the person identifier, the retention window, and any data inclusion rules.

A structured collection of records or events ingested into Adobe Experience Platform from a source. Inside a CJA connection, each dataset supplies fields that become reportable dimensions and metrics.

Experience Data Model schema: the formal definition of fields, data types, and relationships behind a dataset. It determines which fields can be surfaced as dimensions or metrics in CJA.

The identifier used to tie events to one individual across datasets and channels. CJA relies on it for stitching, for the person container in segments, and for deduplicated people metrics.

A named definition of an identifier type, such as email or ECID, including its format and governance rules. Namespaces let CJA recognize that different identifiers can describe the same person.

A CJA capability that links events across datasets by matching a temporary identifier to a persistent person ID within a defined lookback window, enabling combined cross-dataset journey reporting.

The period during which event data remains queryable through a connection. Data older than the window drops out of reporting, so it caps how far back historical and cohort analysis can go.

A configuration layer that decides how connection data is exposed to analysts, including components, session settings, attribution defaults, filters, and time zone. Several data views may share one connection.

A reusable dimension, metric, segment, or date range curated in a data view and offered to analysts in Workspace. Components are the building blocks dragged into tables and visualizations.

A categorical attribute used to group and break down data, such as page name, marketing channel, or country. Dimensions answer the who, what, and where questions in a report.

A numeric value that can be summed, counted, or computed across records, such as sessions, orders, or revenue. Metrics quantify behavior and outcomes and drive the numbers in tables.

A data view rule that creates a new dimension by transforming or combining existing fields, for example grouping page URLs into site sections, without modifying the underlying ingested data.

The practice of selecting, renaming, describing, and hiding data view components so analysts see only approved, clearly labeled fields. It reduces reporting errors and keeps business terminology consistent.

A data view setting that defines how much inactivity ends a session. It changes visit counts, session-scoped metrics, and pathing results in every project using that data view.

The core Workspace visualization for arranging dimensions and metrics in rows and columns. It supports breakdowns, sorting, conditional formatting, and quick inline charting of results.

A container inside a Workspace project that holds visualizations and applies its own date range, segment, and data view context to everything placed within it.

A visualization showing how many people move through a defined sequence of steps and where they drop out, exposing friction points along a conversion path.

A Workspace view of the paths people take into, through, and out of a page or event, showing counts and percentages along each branch of the journey.

A table that groups people by the period when they first performed a chosen event, then tracks their retention or behavior in later periods to reveal loyalty trends.

A named set of inclusion and exclusion rules built on event, session, or person containers that isolates a subset of data for focused reporting, comparison, or publication.

The scope level of a segment: event, session, or person. The chosen container determines which records qualify and how resulting metrics behave in reports.

A segment published from CJA into Adobe Experience Platform so it can be activated in downstream destinations, letting marketing teams target the exact population that was analyzed.

A metric defined by a formula that combines existing metrics, constants, and functions. It produces derived KPIs such as revenue per visit without changing the ingested data.

A rule that distributes conversion credit across the touchpoints a person encountered. CJA offers last touch, first touch, linear, participation, and algorithmic options.

The period before a conversion during which earlier touchpoints stay eligible for credit. Short windows favor recent interactions; long windows reveal upper-funnel influence on the outcome.

A classification of traffic source, such as paid search, email, or social, usually derived from tracking parameters or processing rules. Channels enable acquisition comparison and attribution analysis.

Analysis that unifies data from web, app, call center, CRM, and other sources into one view of the customer path, instead of evaluating each channel in isolation.

The policies and controls governing how data is collected, accessed, retained, and shared. In CJA this spans permissions, retention limits, consent handling, and audit practices.

The rule setting how long data is stored and available for reporting. Retention affects historical depth, cohort analysis, and compliance obligations such as deletion requests.

An Adobe Admin Console construct that grants users access to CJA capabilities and objects, such as data views, projects, or admin functions, based on their role.

A record of administrative and user activity in CJA, including project changes, data view edits, and permission updates, used for compliance reviews and troubleshooting.

A key performance indicator: a metric explicitly tied to a business objective that teams monitor to judge success. Strong KPIs are specific, actionable, and linked to a decision.

A document stating business objectives, KPIs, required data, tracking requirements, and reporting cadence. It aligns technical implementation with what stakeholders actually need to decide.

The staged path people follow toward a desired outcome, such as visit, product view, cart, and purchase. Funnels expose drop-off and help prioritize optimization effort.

The practice of translating analysis into a clear story with context, evidence, recommendations, and next steps, so stakeholders can act on findings instead of merely reading numbers.