Silwood blogs
Unlocking AI Value: Solving Data and Metadata Challenges in the Enterprise
Many enterprise AI projects stall before they start — not due to bad models, but because the data is unclear, incomplete, or inaccessible. This blog explores how poor metadata discovery in systems like SAP, Salesforce, and legacy apps derails progress — and why modern, automated metadata tools are now essential to AI success.
Read the latest blogs from our team
Star Schemas and Snowflakes - Finding data models in SAP BW
Discover a SAP BW data model example showcasing an InfoCube. Safyr® helps you navigate the complexities of BW models for BI.
How to Compare Two Salesforce Systems Using Safyr
Explore Safyr's 'Compare Subject Areas' feature for analyzing metadata differences in ERP and CRM systems, unlocking its potential.
What is a Data Lake and How to Ensure Quality Data Ingestion
Explore the intricacies of data lakes, data contents, and the crucial role of metadata in ensuring data lake projects deliver value.
Understanding Salesforce Metadata with Safyr
Discover why Safyr's Salesforce metadata extraction is gaining popularity despite Salesforce's simplicity. Explore Salesforce data complexity.
Discover How to Efficiently Harvest Microsoft Dynamics Metadata Using Safyr
How Silwood's 'ETL for Metadata' approach was used to map metadata in Microsoft Dynamics CRM applications into the Safyr repository structure.