Data Harmonization in Salesforce Data Cloud: Making Your Data Work for You
“The goal is to turn data into information and information into insight.” — Carly Fiorina, former CEO of Hewlett Packard
The Challenge of Data Chaos
Data is everywhere, flooding our systems and platforms, yet its sheer abundance often leaves businesses grasping at straws for actionable meaning.
A staggering $5.2 million in annual revenue is lost by businesses unable to tap into the power of their data, a missed opportunity hidden in plain sight[i].
The challenge lies not in the absence of data but in its disarray. Without a process to unify and align it, businesses are left navigating silos of information, struggling to piece together fragmented insights.
This is where data harmonization helps connect the dots and draws a clear and actionable picture.
The Knight in Shining Data to the Rescue – Salesforce Data Cloud
With Salesforce Data Cloud, you can unlock the full potential of your data. This platform enables you to integrate, manage, and derive insights from diverse datasets, transforming them into a unified, cohesive view. The physical architecture of Data Cloud is made up of various data objects, and understanding these is crucial as they form the basis for how data is ingested, harmonized, and activated within the platform.
Key Components of Data Cloud Architecture
1. Data Source
This is where data originates from outside of Data Cloud. For example:
- Salesforce platforms (e.g., Sales Cloud, Commerce Cloud)
- Object storage (e.g., Amazon S3, Microsoft Azure)
- APIs, websites, mobile apps, SFTP file transfers
2. Data Stream
A Data Stream is a specific set of data extracted from a Data Source (e.g., ‘Orders’ from Commerce Cloud or ‘Contacts’ from Sales Cloud). It can be categorized as Profile, Engagement, or Other.
3. Data Source Object (DSO)
A DSO is a temporary staging area where raw data from Data Streams is stored in its original format (e.g., CSV). Basic transformations can be applied during data ingestion.
4. Data Lake Object (DLO)
The DLO is the first object ready for inspection, allowing users to map fields and apply additional transformations. It’s stored in formats like Apache Parquet, enabling efficient data storage and retrieval. DLOs are compatible with other cloud providers, allowing for integration with zero-copy architecture.
5. Data Model Object (DMO)
DMOs provide a virtual, non-materialized view of the data lake. They don’t store data permanently but pull real-time data from DLOs when queried. DMOs can be pre-defined or custom, and they support relationships between different data objects.
Now that we understand these components in Data Cloud, let’s see how they work in action.
Consider an example where five essential data tables—Customer Profiles, Orders, Inventory, Payments, and Website Activity—are sourced from an eCommerce platform and a marketing automation tool.
To transform this data into meaningful insights, Salesforce Data Cloud follows a structured process:
- Connect: First, it ingests data from both the eCommerce platform and the marketing automation tool into the Data Cloud, ensuring all five data tables are unified and ready for further processing.
- Harmonize: The next step is mapping the data to the Data Cloud’s unified model, ensuring all streams are aligned and consistent.
- Unify: Through advanced matching rules, you can consolidate the data from both sources into a single, unified customer identity.
- Analyze: With easy-to-use drag-and-drop functionality, you can segment customers based on specific behaviors, such as purchasing patterns or website interactions.
- Act: Finally, the enriched customer data is activated for use in highly targeted, personalized campaigns, optimizing outreach efforts across digital channels.
Data Cloud’s harmonization process brings order to data chaos, allowing you to move from fragmented information to a comprehensive understanding of your business—driving data-driven decisions and actions that propel success.
Let’s understand more about data harmonization, its importance, and how it works within Salesforce Data Cloud.
The Tale of Data Harmonization
Data harmonization is the process of integrating data from multiple sources to function cohesively as if they originated from a single source. While there are different methods to achieve harmonization, one key indicator of success is alignment. If data from multiple sources aligns perfectly at the level of a shared value during visualization, it is considered successfully harmonized at that level.
Why Data Harmonization is Important?
To achieve a truly comprehensive and reliable 360-degree view of your customers, accounts, third parties, and internal resources, data harmonization is essential.
90% of data professionals report that preparing data for analytics is challenging. Data harmonization transforms fragmented data into actionable insights, saving tech teams up to 80% of the time spent on data collection and organization[ii].
Here’s how it helps:
- Breaks Down Data Silos: Struggling with data scattered across different systems? Harmonization brings it all together, giving you a unified, comprehensive view of your customer.
- Improves Data Accuracy: Say goodbye to errors and inconsistencies. Harmonizing your data ensures everything is aligned and accurate, no matter where it comes from.
- Improves Decision-Making: With clean, unified data, you can confidently make decisions based on real insights, not guesswork.
- Drives Personalization: A 360-degree view of your customers means you can create more personalized, targeted marketing campaigns that resonate.
By harmonizing data from various customer touchpoints, businesses can gain a comprehensive view of customer behavior, improving segmentation and targeting. This enables more personalized customer experiences and better product development.
The Voyage of Data Harmonization in Salesforce Data Cloud
Data Cloud, built on Salesforce’s metadata framework, streamlines data integration with intuitive point-and-click mapping and pre-configured bundles. These tools automatically align diverse datasets into a unified model, enabling seamless access and utilization across all Salesforce applications with a complete 360-degree customer view.
- Reference Data Models: Effortlessly transform data from any source into Salesforce-native objects and fields using the standard metadata framework. Get started quickly with ready-to-use reference data models or customize them to fit your specific requirements.
- Build and Deploy Data Graphs: Optimize data for services like AI by making targeted portions of your enterprise data model accessible. Leverage Data Cloud’s visual builder to define and manage relationships between data objects, ensuring improved speed and efficiency before deployment.
Data Cloud integrates data from various sources. Harmonization is what helps in combining and organizing this data into a single format, making it ready for analysis. Here’s how it works.
1. Data Dictionary
The first critical step in data harmonization is mapping the source data. If this step is not executed properly, it can lead to inconsistencies or even incorrect data in downstream processes. To prevent this, it is essential to create a data dictionary for each data source before mapping the data.
A data dictionary outlines the following for each source:
- Data entities
- Attributes
- Context
- Permissible values
By defining these elements upfront, the dictionary supports the data mapping process but identifies common attributes across sources and clarifies their relationships. Once data dictionaries are established, the data mapping process can proceed smoothly.
2. Mapping Data with DMO Concepts
In Data Cloud, data mapping occurs between the Data Layer Objects (DLOs) and Data Model Objects (DMOs). Unlike Marketing Cloud, which allows users to define custom schemas in Data Extensions, Data Cloud uses a highly canonical data model consisting of 89 predefined DMOs designed to accommodate most platform use cases.
These DMOs are structured to fit a wide range of needs, and while custom fields and objects can be added to extend the model, it’s recommended to rely on standard DMOs where applicable. Only extend the model when necessary.
3. Field Mapping Process
Mapping fields from the Data Source Objects (DSOs) to DMOs in Data Cloud is intuitive and straightforward. When creating a data stream, you assign it a category (Profile, Engagement, or Other), and this category determines the type of data the stream will handle.
Once assigned, the category cannot be changed. The categories are inherited by the DMOs, which can only accept data from the same category as the first DLO mapped to it. Some categories, like the Individual DMO, are fixed and always associated with the profile category. Additionally, Salesforce Connectors enforce default mappings that cannot be altered. The result of field mapping is a series of DMOs representing virtual, non-materialized views into the data lake, derived from the physical DLOs.
4. Fully Qualified Keys (FQK)
FQKs are designed to avoid conflicts when integrating data from multiple sources. An FQK is a combination of the source-provided key and a key qualifier, ensuring that data from different sources can be harmonized without key collisions.
In the world of endless data streams and disconnected silos, the journey to harnessing actionable insights feels like chasing constellations in the night sky—dazzling but distant. Salesforce Data Cloud brings that data into reach. As you venture into the evolving landscape of data, remember: the power lies not in the volume of data itself, but in how you harmonize it.
The End of Data Chaos: Real-World Use Cases of Data Harmonization with Salesforce Data Cloud
In this section, we highlight potential use cases that demonstrate how Salesforce Data Cloud can help organizations bring order to their data.
1. Personalized Marketing
A global e-commerce brand integrates customer data from its website, mobile app, and social media platforms using Salesforce Data Cloud. By harmonizing this data, they can create personalized email campaigns and push notifications based on individual browsing habits and purchase history. This unified view helps the marketing team create highly targeted campaigns, delivering personalized offers to each shopper and enhancing engagement.
2. Improved Customer Service
A leading telecom company uses Salesforce Data Cloud to consolidate customer service interactions from email, chat, and call center data. This gives agents a comprehensive, unified view of the customer’s history—such as billing issues or technical support requests—enabling faster, more personalized service.
3. Improved Regulatory Compliance
A financial institution consolidates transaction and client data into Salesforce Data Cloud, ensuring all data is accurate and up to date. This harmonized data is essential for meeting strict regulations like GDPR and CCPA. The company can easily generate reports for audits and track compliance, reducing the risk of fines and maintaining a trustworthy relationship with customers.
4. Enhanced Analytics
A healthcare provider consolidates patient data from their electronic health records (EHR), appointment scheduling, and lab results. With Salesforce Data Cloud, they can run advanced analytics on patient outcomes and predict future healthcare needs, such as identifying patients at risk of chronic illnesses. This drives better resource planning and improves patient care.
5. Optimized Customer Behavior Insights
A global retail chain collects data from POS systems, loyalty programs, and online purchases into Salesforce Data Cloud, harmonizing it into a unified customer profile. Data Cloud ensures this information is accurate, deduplicated, and enriched with behavioral insights, creating a 360-degree view of customers.
This harmonized data is then pushed to Tableau, where interactive dashboards help:
- Visualize customer trends across channels and demographics.
- Identify buying patterns and high-value customer segments.
- Optimize marketing strategies and campaign effectiveness.
Salesforce Data Cloud transforms the way you manage and leverage data, bringing an end to the chaos and empowering your business to unlock new levels of efficiency, growth, and compliance.
Statistical References
[ii] Infoverity