How to set up Assets Data Manager

[#1]

The Assets Data Manager is now in open beta for all users! With the latest capabilities of Jira Service Management Assets, you can ensure that your asset data is complete, correct, and current.

What does Data Manager do?

Data Manager serves as the cornerstone for ensuring the accuracy of your asset and configuration management data when integrating information from various data sources. It provides essential support in the following areas:

• Simplify data ingestion: Integrate multiple data sources into a single source of truth.

• Deliver reliable asset data: Clean, reconcile, and normalize data for consistency.

• Optimize asset processes: Provides in-depth data analysis and dashboards to automate workflows and improve decision-making.

Note: Data Manager feature is exclusively offered with the Premium or Enterprise plans for Jira Service Management Cloud, and it is included at no extra cost in your subscription.

How to get started with Data Manager?

To begin, you need to enable Data Manager in your instance and configure the necessary permissions.

You can either watch this informative video: How to enable Data Manager in your instance and set permissions or follow the steps outlined below:

Go to Assets settings:

To enable Data Manager, first, navigate to the Data Manager tab. Then, toggle the “Turn on Assets Data Manager” option to activate it and configure the necessary permissions. After completing these two steps, you are ready to begin setting up Data Manager.

Please be aware that your Data Manager instance will initially appear empty. This is because you need to configure the data source integrations, as well as address the mapping, cleansing, and reconciliation processes. Additionally, you will need to set up analysis and dashboards.

How to configure Data Manager?

Configuring Data Manager involves four key steps, outlined below:

1. Integrate: Set up jobs to ingest data into Data Manager.

2. Cleanse and Reconcile: Establish attribute mapping, eliminate unnecessary data, define the normalization process, and consolidate the data into the appropriate objects.

3. Import to Asset Schemas: Transfer only the relevant data to the schemas.

4. Optimize: Create searches and dashboards to analyze the data effectively.

For an overview, watch this video that outlines the steps to configure Data Manager: Data Manager flow and how to configure [15 min].

Data Manager How-to videos

Below is a collection of brief videos designed to help you get started with configuring Data Manager:

Step	How to video	Related Documentation
Enable Data Manager	How to enable Data Manager in your instance and set permissions [3 min]	Enable Data Manager
1 - Integrate	How to create a job using a Flat File adapter [5 min] How to create a job using the Lansweeper adapter [5 min]	Create a job to ingest data Move data into Data Manager to create raw data Learn about Adapters
	How to run a job [5 min]	Run a job Download Data Manager clients
	How to transform the data [5 min] - optional step.	Transform data Transformation functions
	Automating data ingestion (refer to the documentation)	Automating data ingestion
2 - Cleanse and Reconcile	How to map the data [5 min]	Mapping data sources to an object Check the Data Manager out-of-the-box Object classes
	How to cleanse the data [4 min]	Configure cleansing rules Cleanse your data
	Normalizing data ( refer to the documentation)	Compute Dictionaries Configure Custom Computed Dictionaries
	How to reconcile the data [2 min]	Reconciling data from multiple sources (it is called “Import”)
	Automating cleansing and reconciliation (refer to the documentation)	Cleanse your data using the Cleanse and Import client for MacOS Cleanse your Data using the Cleanse and Import Client for Linux Cleanse your data using the Cleanse and Import client for Windows/DOS
3 - Import Data Manager data to schemas	Create searches (refer to the documentation)	Create searches
	Import data into schemas (Native Data Manager importer feature - coming soon) Please refer to the documentation for other options.	Import data into schemas using CSV data Import data into schemas (Native Data Manager importer feature - coming soon)
4 - Optimize	Create searches (refer to the documentation)	Create searches
	Create dashboards (refer to the documentation)	Create dashboards

Data Manager in-product Setup Guide

An alternative way to learn how to set up Data Manager is by following the in-product setup guide.

To access the Data Manager in-product guide, simply click on the “Import and Analysis” menu option. From there, you can easily navigate through the various stages to set up Data Manager.

Important note:

Configuring Data Manager is a one-time process. You will only need to adjust the settings when introducing new data sources, modifying attributes, or creating new normalization tables, among other scenarios.

Want to learn more about how Data Manager helps?

• Visit atlassian.com/datamanager

• Watch the Data Manager overview demo [15 min].

Additional videos:

• Data Manager overview [2 min]

• Data Manager tour [10 min]

Important Notes: Data Manager is a powerful tool designed for integrating, consolidating, and analyzing data; however, it should be noted that it is not intended for discovery purposes.

Share your thoughts and experiences in the comments below!

Happy to help!

Silvia A, Davis - Sr. Technical Product Marketing Manager

[Matthew]

I tried it out last week and honestly, once you get through the initial setup, it’s pretty smooth. The cleanse and mapping parts need a bit of trial and error, but the UI is straightforward.

[Silvia Davis]

I am glad you have set it up @Matthew ! It is a powerful capability. 

[Roger]

What are some examples you can use Data Manager for? Thank you.

[Silvia Davis]

Excellent question @Roger !

If you have multiple data sources, such as a discovery tool, MS Entra ID, and Jamf, you can integrate them seamlessly into Data Manager. This tool enables you to cleanse unnecessary data, reconcile discrepancies, and selectively bring only the data you need into schemas. By doing so, Data Manager ensures your asset data is not only accurate and reliable but also tailored to your specific requirements.

In addition to being an integration tool, Data Manager supports ongoing data quality by maintaining consistency and reliability. For example, by comparing security and patch management systems with your asset data, you can proactively identify and address potential security vulnerabilities.

Check this videos for more details:

• Data Manager overview [2 min]

• Data Manager overview demo [15 min]

• Data Manager tour [10 min]

Let me know if that helps.

[Roger]

Hello Silvia, thank you for your reply. The overview demo (15 minutes) was helpful, because it made it more specific for me, because I saw how it works and how you could use it as an example.

[Aaron Geister _Trundl_]

A few things I think about!

This is for some teams and not all. It would be a good option if you could run the agents from cloud rather than from a server or device. I understand that this has to do with control of data and security in some aspects but for those that use Saas having the ability to run in the Atlassian site makes more since since its really just a token pull data from a source. 

The other thing I am curious about. Did the team release the ability to push the data to the schema's? If so thank you but I wasn't seeing it.

[Piyush Annadate _ACE Pune_]

A good article to read -> Process -> Follow and Learn specially !! 

[Silvia Davis]

Hi @Aaron Geister _Trundl_ great point about running the clients directly from JSM Cloud. We have an open ticket, and I encourage you to vote for it if you have the chance.

Regarding the Data Manager native importer to schema, it's coming soon. In the meantime, please refer to step #3 in the process for an alternative option.

Thank you again for your questions!