AMA Post event: Explore the New Assets Data Manager: Key Takeaways from Our AMA

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If you missed our event “Let’s Talk Assets!” AMA, here’s the short version: the new Assets Data Manager experience is faster to navigate, easier to understand, and designed to help teams bring scattered asset data together into one trusted view.

In this virtual session, we walked through the redesigned Data Manager UI, explained updated terminology, and showed a live end-to-end workflow for fetching, transforming, reconciling, and importing data into Assets in Jira Service Management.

Why it matters: Data Manager helps you unify data from multiple sources, improve data quality, and build a more reliable foundation for asset and service operations.

What we covered in the AMA

The session focused on the biggest changes in the new Data Manager experience and how those changes support real-world asset management use cases.

A redesigned UI with clearer navigation

One of the biggest updates is the new navigation model. Data Manager now centers around three main areas:

• Getting Started for onboarding and setup guidance

• Object Classes for managing the structure and attributes of your data

• Data Visualization for exploring results and building dashboards

This new layout makes it easier to move from setup to analysis without jumping across disconnected screens.

Updated terminology that better matches the experience

We also highlighted a few terminology changes that make the product more intuitive:

Old Terminology	New Terminology	What it means now
Analysis	Object classes	Where you manage the structure of your data.
Dashboards	Data visualization	View your data insights.
Adapters	Add a data source	The simple action of connecting external data.
Jobs	Data sources	No more "Jobs"—just manage your sources directly.
Run a job	Fetch	Directing the client to get data from the source.
Import	Merge	Combining your various data sources into your object class.
Compute Dictionaries	Data dictionaries	Rules used to normalize and clean your incoming data.
Staging Data	Raw / Transformed / Cleansed	Clearer stages showing exactly what state your data is in.

An end-to-end demo of the Data Manager workflow

The AMA included a live walkthrough of the core workflow using a Lansweeper data source. We demonstrated how teams can move from raw data to usable asset records through a structured process:

1. Add a data source
2. Fetch data from a connected source
3. Prepare data

   1. Transform values, such as concatenating fields or converting data types

   2. Map only the source attributes you actually need

   3. Cleanse records by removing duplicates or rows missing primary keys

   4. Merge data across sources to create a more complete and trusted record

4. Create searches or import the data to schemas

Best practice shared during the demo: map only the attributes you need and import only the records you intend to manage in Assets. This keeps schemas cleaner and makes reconciliation easier to maintain.

Searches, saved searches, and dashboards

Another major topic was how to turn reconciled data into actionable insight. We showed how to:

• Create searches within an object class

• Save filtered searches for reuse

• Limit what gets imported into schemas

• Build dashboards with visualizations such as stacked bar and pie charts

This helps teams quickly spot gaps, overlaps, and discrepancies across their data sources, such as devices missing key controls or records appearing in one source but not another.

Importing Data Manager results into Assets schemas

We also walked through how Data Manager connects to Assets schemas, including the Common Data Model content. In the demo, we showed how to:

• Select a saved search as the source for import

• Choose the target object type in Assets

• Map Data Manager attributes to schema attributes

• Enable the import and populate objects and relationships

A key takeaway from the Q&A: relationships are driven by schema modeling and attribute references, so when imports are configured correctly, related records can be populated automatically.

Important note: what counts toward usage is what you import into Assets schemas, not every record that exists inside Data Manager.

Why you should try Data Manager

If your asset data lives across multiple systems, spreadsheets, or tools, Data Manager can help you bring that information together into a more complete and trustworthy source of truth.

That can mean:

• Better visibility into your environment

• Cleaner, more reliable asset data

• Easier identification of risk, compliance gaps, and cost-saving opportunities

• Smarter reporting and richer service context in Jira Service Management

How to enable Data Manager in your JSM instance

If you are ready to explore it yourself, here is the basic setup flow:

1. Open Assets in Jira Service Management.

2. Go to Settings or the relevant configuration area.

3. Select Data Manager from the Assets or app settings menu.

4. Turn on the Assets Data Manager toggle.

5. Under access settings, add yourself and any relevant teammates to the appropriate admin roles, including Data Manager admin and Adapter admin, so you can fully configure and manage data sources.

Depending on your environment and available connectors, some data sources may support cloud-based fetching directly in the UI, while others may still rely on the Data Manager client.

What’s next

We’ll continue sharing guidance and resources to help teams get started, including recordings, walkthroughs, and how-to content. If you want to learn more, try enabling Data Manager in your instance and start experimenting with fetching, cleansing, visualizing, and importing your own data.

The new experience is built to make that journey simpler.

References and How to videos

• Replay: AMA: Let’s Talk Assets! Explore the New Data Manager UI & Get Your Questions Answered

How to videos:

• Data Manager - How to enable Data Manager in your instance
• Data Manager - How to ingest data into Data Manager
• Data Manager - How to ingest data from a flat file
• Data Manager - How to fetch data using the Data Manager client
• Data Manager - How to prepare your data (transform, map, cleanse, merge)

Thank you again for joining!

Silvia Davis - Sr. Tech Product Marketing Mgr.

Tori Stitt - Sr. Product Marketing Mgr.

Service Collection 

[Brendan Dwan]

Great video. Happy to see the updates.  Is "Schema" a cloud-to-cloud or do we still need to use the CLI to fetch from JSM Asset?