Domain metadata is critical
Even though you may have located and accessed target metadata or data, generating onward value from your data is only achievable if you can provision your information to other environments. The key to that lies in metadata and a consistent understanding of your data domain. That is achieved through metadata, itself understood in the context of an ontology (the pursuit of knowledge), which then enables shared understanding of meaning to be used across and beyond your domain. Metadata is the key which unlocks that knowledge, potential value and enables a functioning ecosystem. Once you can visualise your metadata, much that was impenetrable and difficult (in project terms) opens up. Typical projects could be:
- An enterprise data catalogue or model;
- A governance platform or compliance initiative;
- An enterprise metadata management system;
- A data warehouse;
- Data curation;
- The deployment of ETL or data modelling tools;
- Data migration, consolidation or rationalisation;
- System integration, particularly involving ERP or CRM applications;
- An AI or ML project;
- Semantic metadata deployment;
- Harmonising taxonomies;
- Resolving master data from different departments or applications into domain-wide coherence.
And don't overlook the data or content you may have in storage! Data doesn't just need to be backed up, it needs to be archived - backups are part of your domain too! Does your stored or historic data have metadata that makes it discoverable or targetable? Data science, AI or ML programs are informed by valuable historic data for comparative purposes. But you need to be able to target and filter it, and it needs to retain its provenance, context and relationship so that retains its value.