Our Data Health Reports package offers 110 reports that give you key insights into your data’s health, reliability, and usage trends. These reports help you assess data quality and spot issues like duplicate values, picklist usage, data governance gaps, and default value usage. Use these reports to:

Table of Contents

Data Health Reports and the Profiling Definition Category

Reports in the Data Health Reports package only display results from profiling definitions categorized as Baseline. If you don't see the expected results in your reports, verify that your profiling definitions are assigned to the Baseline category.

For more information on assigning a category to a profiling definition, refer to Create a Profiling Definition, where we explain how to describe the profiling definition.

Report Types

Reports available in the Data Health Reports package are all custom report types based on the custom objects installed with Cuneiform for CRM: Field and Data Management. Refer to Cuneiform for Salesforce Custom Objects for more information on our custom objects and their fields.

Reports

Our Data Health Reports are organized into groups by data health topic, each containing categories with individual reports.

Field Utilization and Optimization

This group of report categories helps you optimize underused fields and manage metadata dependencies in your Salesforce org. It highlights low-population fields for cleanup and deprecation while offering insights into dependencies like UX, reporting, and workflows. These reports simplify your data, boost system performance, and improve the overall user experience.

Low-Population Fields

Our Low Population Fields reports help you identify underutilized custom fields across your org by analyzing field usage patterns and metadata characteristics. With these insights, you can develop a data-driven cleanup strategy to reduce org complexity and optimize storage while preserving essential functionality.

Unpopulated Fields

Our Unpopulated Fields reports help you identify fields without data, revealing gaps in data collection processes and user adoption patterns. These insights enable you to develop targeted strategies for improving data quality, including focused user training programs and process improvements.

Metadata Dependency

Our Metadata Dependency reports help you visualize how your fields interconnect with workflows, layouts, validation rules, and other critical components across your org. These insights enable you to assess potential impacts before making system changes and ensure safe field deprecation processes.

Duplicates and Identity Resolution

This group of report categories helps you tackle duplicate values and identity resolution in your Salesforce data. It identifies fields with high duplicate density, helping you prioritize deduplication efforts and improve match rules. Additionally, the reports assist with Salesforce Data Cloud implementation by pinpointing fields ideal for identity resolution, which is crucial for creating a unified customer view. These insights streamline data prep and enhance record-matching accuracy.

Duplicate Values

Our Duplicate Values reports help you analyze where and how frequently duplicate values occur across your fields, enabling you to identify high-impact areas for data cleanup. These insights help you optimize matching rules and strengthen your overall deduplication strategy based on concrete evidence.

Identity Resolution

Our Identity Resolution reports help you analyze the quality and matching potential of contact point data (addresses, emails, phones, URLs) across your customer records. These insights enable you to optimize matching strategies and build a more accurate 360-degree customer view while maintaining data privacy and compliance.

Picklist/Field Values and Record Type Usage

This group of reports helps you optimize picklist fields, default values, and record types in your Salesforce org. It identifies active and inactive picklist values, non-picklist fields for conversion, and areas to improve consistency. The reports also analyze default value usage to help streamline data entry and ensure configurations meet business needs. The record type analysis also provides insights into usage patterns, enabling you to refine processes, optimize object schemas, and enhance data quality. These tools boost efficiency, data accuracy, and CRM adoption.

Picklist Fields and Values

Our Picklist Fields and Values reports help you analyze how active and inactive picklist values are being used across your org, revealing opportunities for consolidation and standardization. These insights enable you to streamline data entry processes and improve reporting accuracy by optimizing your picklist value sets.

Default Values

Our Default Values reports help you analyze where default field values are being used effectively across your org to automate data entry and maintain consistency. These insights enable you to identify opportunities for additional automation and standardization that can improve data quality while reducing manual effort.

Record Types

Our Record Type Usage reports help you analyze how different record types are utilized across your org, revealing adoption patterns and population trends. These insights enable you to optimize your record type strategy and make informed decisions about business process improvements and data organization.

Profiling Segments and Value Outliers

This group of reports helps you dive deeper into Salesforce data by focusing on critical fields for profiling and identifying outlier values. The reports highlight fields that need closer examination, aiding segmentation and targeted data governance. They also pinpoint unusual field values that deviate from the norm, helping teams prioritize data-cleansing efforts. These insights boost data quality, improve reporting accuracy, and enhance overall CRM data management.

Profiling Segments

Our Profiling Segments reports help you analyze data patterns and variations across your org to identify your most impactful data segments. These insights enable you to develop targeted data quality strategies and governance initiatives based on clear patterns and priorities.

Outlier Values

Our Outlier Values reports help you identify unusual data patterns and anomalies that could indicate data entry errors or process breakdowns. These insights enable you to proactively address data quality issues before they impact your business processes.

Data Governance and Data Dictionaries

This group of reports focuses on Salesforce data governance, object relationships, and field documentation. It helps you analyze field usage, data ownership, and sensitivity levels, empowering teams to strengthen governance strategies and ensure compliance. The reports also reveal how Salesforce objects are interconnected, highlighting data gaps and optimizing cross-object reporting. Additionally, insights into field descriptions and help text allow administrators to fill documentation gaps, improving data quality, user adoption, and overall governance. These tools enhance data management and create a well-structured, compliant Salesforce environment.

Data Governance

Our Data Governance reports help you evaluate your data protection measures by revealing gaps in governance controls and analyzing field sensitivity patterns. These insights enable you to strengthen your security controls, maintain compliance requirements, and better protect sensitive data.

Object Reference

Our Object References reports help you analyze how objects are connected and referenced throughout your system by mapping relationships between objects and their associated fields. These insights enable you to optimize your data model, maintain data integrity, and improve system performance.

Data Dictionary

Our Data Dictionary reports help you assess the completeness of your system documentation by analyzing where field descriptions and help text exist or are missing across your org. These insights enable you to improve documentation quality to better support user adoption, training, and system governance.

Record Ownership and Namespace Usage

This group of reports focuses on user interactions and namespace management in your Salesforce org. It provides insights into record ownership, creation, and modification patterns, helping administrators and data quality teams improve data stewardship, track critical contributors, and optimize user permissions. Additionally, the reports analyze field distribution and usage across different namespaces, offering a holistic view of object composition. These insights help teams streamline data models, manage namespace usage, and ensure the efficient use of Salesforce resources.

Owners, Creators, and Modifiers

Our Owners, Creators, and Modifiers reports help you analyze patterns in how your data is being created, modified, and maintained by revealing user engagement patterns across objects. These insights enable you to understand data stewardship patterns, support audit requirements, and optimize sharing settings.

Namespaces

Our Namespaces reports help you examine how fields are being utilized across different managed packages by analyzing population patterns and object distribution. These insights enable you to streamline package management, plan upgrades, and improve system efficiency.

Cuneiform Profiling Templates

This group of reports includes pre-built templates for comprehensive data quality and reliability assessments in Salesforce. These templates provide a strong starting point for creating custom reports and dashboards tailored to data reliability needs. Additionally, the Profiling Exceptions Analysis reports categorize exceptions during data profiling, offering detailed insights into issues with fields, objects, and profiling definitions. Salesforce administrators can use these reports to identify recurring problems and streamline troubleshooting efforts quickly.

Data Health Report Templates

Our Data Health Report Templates provide foundational building blocks for your data quality program by offering adaptable models for analyzing field values, record types, and profiling results. These customizable templates enable you to jumpstart quality initiatives and establish monitoring processes tailored to your organization's specific needs and standards.

Profiling Exceptions

Our Exception Logs reports help you monitor and troubleshoot data profiling processes by exposing where issues occur or unexpected results are produced. These insights enable you to maintain reliable data quality metrics, improve profiling accuracy, and optimize your profiling configurations.