AI-Ready Enterprise Data
Organizations that gain the most from SAP's AI-driven future will be
those built on trusted data. Your AI is only as good as the data behind it.
Building the AI-Ready Data Framework
to Power Your Autonomous Enterprise
Create the trusted data foundation needed to power AI, analytics, and intelligent business decisions.
Challenges
Data quality challenges faced by organizations.
Building the AI-Ready Data Framework
to Power Your Autonomous Enterprise
Create the trusted data foundation needed to power AI, analytics, and intelligent business decisions.
Outcomes
Value delivered through data quality enablement.
Building the AI-Ready
SAP Enterprise
Organizations can no longer view governance, quality, analytics, and AI as separate initiatives. Instead, they should approach them as a connected enterprise data strategy. This strategic enablement framework governs transactional data, creates enterprise-wide data transparency, and unifies trusted data for AI and analytics.
What customers are saying about Auritas...
With over $2 billion in cumulative customer savings, Auritas' data
volume management solutions deliver measurable business outcomes.
Data Quality Assessment
Start with a comprehensive assessment of enterprise-wide data quality to establish a trusted foundation for AI, analytics, and business transformation. Understand where you stand and next steps on how to improve quality.
Explore Resources
Webinar | Data Governance for SAP Users Preparing for AI
Explore why data quality and governance have are critical for organizations navigating SAP transformation and AI adoption.
What is Data Governance Maturity Assessment?
Explore what is and how this systematic evaluation of your data governance framework workd.
Standardize Data Governance For Large-Scale Merger
Implementing standardized processes and a centralized data source, improves accuracy, planning, and procurement.
Mastering Data Governance: Building Blocks for Data Success
Gain a solid foundation for implementing successful data governance practices tailored to your specific context.
Master Data Governance for Your SAP Cloud Environment
As organizations accelerate their journey to the cloud, implementing a tool for master data governance is critial.
E-book | Data Governance: Developing a Framework
Explore the intricacies of a well-established data governance program with key considerations, best practices, and practical tips
Data Quality & AI - FAQs
How do organizations prepare SAP data for AI?
Organizations prepare data for AI by assessing data quality, standardizing formats, and defining clear governance rules. Clean SAP data gives AI tools stronger inputs for reporting and automation. Identifying data issues early on can help teams take action before errors start affecting AI outcomes.
How does data quality support SAP Business AI and Joule?
Data quality supports SAP Business AI by giving tools, like Joule, accurate, consistent information to work from. Clean customer, vendor, material, and finance data helps improve recommendations, search results, summaries, and automated workflows across SAP environments.
How does data quality impact AI accuracy?
AI accuracy depends on the quality of the data feeding the model. Duplicate, incomplete, or outdated ERP data can lead to weak outputs, missed patterns, and lower user trust. A trusted data partner helps organizations find and fix quality issues before AI adoption.
How does SAP Master Data Governance (MDG) support AI readiness?
SAP Master Data Governance (SAP MDG) supports AI readiness by creating stronger control over master data rules, quality standards, and changes. With cleaner SAP data, organizations can reduce risk and build a stronger foundation for automation, analytics, and AI use cases.