Experian Data Quality
Better data quality, backed by Experian data and expertise, for the way your business works.
Move from data quality to data intelligence
Aperture Data Studio is Experian’s data intelligence platform for understanding, improving, connecting and governing data across complex environments.
The platform brings together data quality, catalogue, governance, lineage and observability capabilities, helping teams prepare more consistent, connected and understood data for AI, reporting, risk management and other critical business initiatives.
Improve the data you already have
Identify outdated, incomplete, inconsistent and duplicate records across through data cleansing and remediation services.
Validate and enrich customer data
Check and standardise postal addresses, email addresses, phone numbers, and add relevant information to support more complete customer and business records.
Connect and unify customer data
Use data matching to link fragmented records across different systems and support a Single Customer View.
Strengthen data governance
Improve visibility of critical data, defined quality standards and relevant monitoring measures.
Connect data quality into everyday workflows
Embed supported data quality capabilities into Salesforce, Microsoft Dynamics, SAP, Snowflake, Shopify and other compatible business applications your teams already use
Support better customer experiences
Help teams use more accurate and complete information across customer interactions.
Support operational efficiency
Help reduce the time and effort spent managing duplicate, incomplete and inconsistent data.
Support more informed reporting
Help teams work with more accurate and consistent information across systems and functions.
Prepare data for AI and analytics
Help address the quality, consistency and connectivity of data used in AI, reporting and analytics initiatives.
Backed by Experian data
Use relevant Experian data, including Bureau, segmentation, identity and fraud data where available, alongside selected third-party sources to validate, enrich and supplement customer and business records.
Expertise to shape your approach
Work with data quality consultants to assess your requirements, identify potential issues and develop an approach aligned with your priorities.
Supported by Experian security standards
Our solutions is developed and managed using relevant Experian security standards, with controls designed to protect data across supported environments.
Designed to work with your ecosystem
Our solutions are API driven so they can seamlessly integrate with your existing systems and platforms.
Not sure where to start?
A Data Health Check can help you assess selected data, identify potential quality issues and determine which areas may warrant further attention.
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Frequently asked questions
Data quality describes whether information is sufficiently accurate, complete, consistent, current and valid for its intended use. The measures used to assess data quality depend on the dataset, the business process it supports and how the information will be used.
Organisations use data across customer interactions, operational processes, reporting, governance, analytics and AI initiatives. Incomplete, outdated, inconsistent or duplicate information can create additional work and make data more difficult to understand, connect and use.
Common data quality issues include incomplete fields, outdated customer details, inconsistent formats, invalid contact information, duplicate records and fragmented information held across different systems. These issues can arise as data is captured, updated, transferred and used over time.
An organisation can assess data quality by profiling selected datasets against defined measures, reviewing completeness and validity, identifying inconsistencies and examining potential duplicate records. Relevant data quality processes may then include validation, cleansing, standardisation, enrichment, matching and ongoing monitoring.
Data intelligence brings together data quality, catalogue, governance, lineage and observability capabilities to help organisations understand, connect and manage data across complex environments. It provides context about what data means, where it comes from, how it changes and how it may be used.
Data quality focuses on the condition of data, including its accuracy, completeness, consistency and validity for an intended use. Data intelligence builds on this foundation by adding catalogue, governance, lineage and observability capabilities that help organisations understand and manage data more broadly.
Data quality and data intelligence can help organisations assess the quality, context, lineage and governance of data intended for AI. These capabilities can support data preparation and ongoing monitoring, but do not guarantee the accuracy, performance, fairness, security or suitability of an AI system.
Aperture Data Studio is Experian’s data intelligence platform for understanding, improving, connecting and governing data across complex environments. It brings together data quality, matching, transformation, catalogue, governance, lineage and observability capabilities in one platform.