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Explore the New Data Manager UI &amp; Get Your Questions Answered","description":"The meeting presented the redesigned Assets Data Manager UI, highlighting terminology changes (adapters→data sources, ingest→fetch), a simplified menu, and cloud-enabled connectors that allow in‑UI fetches. Silvia demonstrated end-to-end workflows: fetching from a discovery tool, transforming, mapping, cleansing, merging data, creating saved searches and dashboards, and importing selected data into Assets schemas. Key next steps: use cloud-enabled adapters where available, schedule refreshes for regular imports, and consult provided how-to videos and blog for setup and deeper guidance.\n\n### Data manager purpose and capabilities 2:34\n\n- Data Manager ingests data from multiple sources (discovery tools, CMDBs, endpoint solutions, ERP, databases, flat files) to normalize, transform, reconcile and merge for reliable asset data.\n- The tool addresses gaps where discovery tools lack complete coverage by consolidating attributes from disparate systems (examples: Intune, Azure AD, endpoint tools).\n- Core workflow remains ingest/transform/merge/view, but terminology and UI flow changed to improve admin experience.\n\n### New ui navigation and object classes 6:06\n\n- Main Data Manager menu reorganized: Get started, Object classes, Data visualization, and Settings.\n- Object classes now surface five out-of-the-box classes (Compute, Network, People, Peripherals, Software); attributes within these classes are fully editable though creating new object classes is not yet available.\n- Data sources replaced the previous 'adapters' terminology; object class view now shows available data sources per class for clearer configuration and ingestion.\n\n### Data sources and cloud-enabled connectors 10:49\n\n- Over 20 built-in data sources are available (examples: Lansweeper, SCCM, ServiceNow, Intune, Azure AD); some connectors are marked cloud-enabled.\n- Cloud-enabled data sources allow fetching data directly from the Data Manager UI without using the external Data Manager Client.\n- Connector configuration tests the integration immediately on save; non-cloud connectors still require the Data Manager Client for fetches.\n\n### Live fetch and transform demonstration 20:11\n\n- Demonstrated fetching data from Lansweeper using 'Fetch from the Cloud' to bring raw records into Data Manager.\n- Transform step examples: concatenating fields to create a 'type' field and converting string fields to date/time formats; transforms run immediately and create new transformed columns.\n- UI shows raw, transformed and audit logs for ingestion; transforms are applied before mapping and cleansing.\n\n### Mapping, cleansing and merging workflow 22:54\n\n- Mapping: select only needed attributes from a data source to map into the object class; unmapped attributes can be omitted to avoid clutter.\n- Cleansing: recommended rules include removing records with missing primary keys and deduplicating primary keys; cleanse execution reports counts for eliminated and retained records.\n- Merge: Fetch/Transform/Map/Cleanse/Merge are accessible on one screen; merge reconciles records across sources, applies attribute priority, normalizes via dictionaries, and produces consolidated object records.\n\n### Searches and data visualization 28:14\n\n- Saved searches can filter merged object records (examples: records present in specific sources or missing antivirus) and are used as inputs for imports and charts.\n- Dashboards: create dashboard groups, add charts using saved searches and select chart type (bar, pie, Venn diagram); charts are based on object class attributes (e.g., OS version, data source).\n- Visualizations help identify discrepancies across sources (counts, missing fields, percentage at risk) to prioritize data remediation.\n\n### Schemas and importing data manager data into assets 36:09\n\n- Assets schemas (EAP) follow a common data model: system schemas include people, hardware assets, geography, external organizations; hardware assets include end-user compute, infrastructure, network, peripherals, models.\n- Import workflow: create Data Manager import, select a saved search, choose whether to auto-create object types/attributes or map manually (manual mapping recommended), then map Data Manager attributes to schema fields and enable import.\n- Imported records populate schema objects and relationships pre-modeled in Assets; import logs show history and enable auditability of imports.\n\n### Relationships, modelling and q&a 43:23\n\n- Relationships are not separately imported; Assets uses predefined schema relationships and attribute references so imported data populates relationships automatically when attributes reference related objects.\n- Best practice: perform modeling and import order (e.g., import chassis, models, OS, services separately) so referenced objects exist and relationships materialize.\n- Q&A highlights: custom object classes cannot yet be created (roadmap item), scheduling refreshes (daily/weekly/monthly) is supported, and Data Manager imports into schemas are the ones counted for usage.\n\n### Closing, resources and next steps 50:47\n\n- Silvia apologized for the Zoom glitch, confirmed session recording and availability of how-to videos and a blog post with step-by-step setup (~15 minutes total video length).\n- Next steps encouraged: use cloud-enabled adapters where possible, schedule refreshes for automated imports, and consult provided materials if any step needs repetition.\n- Action items: attendees to review blog/how-to videos, consider import/mapping strategy for their schemas, and expect schema features (hardware assets table) and custom object class support in future releases."}