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Object Modeling in Data Cloud

The Customer 360 Data Model is an intricate structure that harbors various types of data objects. Each object type serves a unique functionality in data management, contributing to the overall versatility and efficiency of the Model. This article deep-dives into four fundamental data object types of the Customer 360 Data Model: Data Lake Object (DLO), Data Model Object (DMO), Unified Data Model Object (Unified DMO), and Calculated Insight Object (CIO).

Data Objects and Their Functions

Data Lake Object (DLO) is an integral component of the data management framework. Serving as a container, a DLO essentially houses all data poured into the Data Cloud. Therefore, it is fundamental to the entire data ingestion process, acting as the preliminary storage location before further data processing and analysis.

Proceeding to the next level, we have the Data Model Object (DMO). This data object provides a harmonious grouping of data sourced from various streams and insights. After data has been ingested and stored in a DLO, its standardization occurs by being mapped to a DMO through the Customer 360 Model. This step enhances the relevance and coherence of the ingested data, paving the way for more sophisticated and precise analyses.

For a more streamlined and consolidated perspective, the Customer 360 Data Model introduces the Unified Data Model Object (Unified DMO). This object represents a DMO that carries unified data. Using identity resolution rulesets, the Model unifies the diverse data present within a standard DMO to create Unified DMOs. In essence, Unified DMOs serve as a hub for commonplace and harmonized data, acquired post the unifying process of varying data.

Finally, in the list of data objects, we have the Calculated Insight Object (CIO). As the name suggests, a CIO is essentially a calculated multi-dimensional metric derived from the entire digital state stored within the Data Cloud. CIOs can encapsulate various metrics including but not limited to metrics like Customer Lifetime Value (LTV), Most Viewed Categories, and Customer Satisfaction Score (CSAT) curated at varying levels including profile, segment, population, or other specialized metrics as preferred.

To summarize, each of these data objects caters to different stages of data management, starting from the point of raw data ingestion via DLOs, to achieving organized data through DMOs, unified insights via Unified DMOs, and calculated metrics through CIOs. The collective functioning of these objects results in insightful and actionable data, thereby contributing to comprehensive customer understanding and effective decision-making.

Keywords: Customer 360 Data Model, Data Lake Object (DLO), Data Model Object (DMO), Unified Data Model Object (Unified DMO), Calculated Insight Object (CIO)

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