AJ-28011 How-to integrate Oracle Analytics with JMS

java-management-oac-integration/build-custom-inventory-dashboard/build-custom-inventory-dashboard.md

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+# Lab 6: Build a Custom Inventory Dashboard
+
+## Introduction
+
+In this lab, you will open the imported JMS inventory workbook in Oracle Analytics Cloud (OAC) and learn how to customize the dashboard to better visualize and analyze your Java inventory data.
+
+*Estimated Time:* 10 minutes
+
+### Objectives
+
+* View the imported inventory workbook and understand its components.
+* Customize the dashboard by modifying visuals, filters, or layout to meet your analysis needs.
+
+### Prerequisites
+
+* JMS inventory template imported into your OAC environment.
+* Access to your OAC instance with permissions to view and edit dashboards.
+* Connection to your Autonomous Database has been established.
+
+## Task 1: View the Imported Inventory Workbook
+
+1. Log in to your Oracle Analytics Cloud (OAC) environment.
+2. From the home page, click **Catalog** in the navigation menu.
+   ![OAC Catalog](../common/images/analytics-cloud-config-catalog.png)
+3. Find and open the JMS Inventory workbook you previously imported and click on it.
+   ![Open Inventory Workbook](../common/images/catalog-jms-data-viewer.png)
+4. Explore the dashboard tabs, visualizations, and filters provided in the default template.
+   ![Sample Default Dashboard](./images/catalog-jms-data-dashboard.png)
+
+## Task 2: Customize the Inventory Dashboard
+
+1. With the inventory workbook open, click **Edit** to enter dashboard editing mode.
+   ![Edit Workbook](./images/catalog-jms-data-viewer-edit.png)
+2. Modify or add new visualizations (charts, tables, maps) to highlight metrics important to your use case.
+3. Change filters, dashboard layout, colors, or visual properties to match your organization’s style or focus.
+4. Save your changes as a new version or overwrite the existing workbook as needed.
+   ![Save Customized Dashboard](./images/catalog-jms-data-viewer-save.png)
+
+## Next Steps
+
+* Continue refining your dashboards and analytics based on feedback from stakeholders.
+* Explore OAC’s advanced features, such as calculations, data flows, or automated insights.
+* Proceed to the next lab for publishing and scheduling dashboards if available.
+
+Congratulations, you completed the lab! You may now [proceed to the next lab](#next).
+
+## Learn More
+
+* [Build Reports and Dashboards](https://docs.oracle.com/en/cloud/paas/analytics-cloud/build-reports-and-dashboards.html)
+
+## Acknowledgements
+
+* **Author** - Maria Antonia Merino, Java Management Service
+* **Last Updated By/Date** - Maria Antonia Merino, January 2026

java-management-oac-integration/connect-oac-to-atp/connect-oac-to-atp.md

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+# Lab 7: Connect Oracle Analytics Cloud (OAC) to Autonomous AI Database
+
+## Introduction
+
+In this lab, you will configure Oracle Analytics Cloud (OAC) to connect to your Autonomous AI Database. This connection enables real-time analytics, dashboards, and reporting using data from your Autonomous AI Database instance.
+
+*Estimated Time:* 10 minutes
+
+### Objectives
+
+* Configure OAC to securely connect to your Autonomous AI Database.
+* Test the database connection from OAC.
+
+### Prerequisites
+
+* Autonomous AI Database instance available with appropriate privileges and credentials.
+* Oracle Analytics Cloud (OAC) instance, set up in the prior labs.
+* OAC user account with data modeling or connection privileges.
+
+## Task 1: Prepare Autonomous AI Database Connection Credentials
+
+1. In the Oracle Cloud Console, open the navigation menu, click **Oracle AI Database**, then select **Autonomous AI Database** .
+   ![Configure Autonomous AI Database](../common/images/configure-autonomous-ai-database.png)
+2. In the database list, locate your Autonomous AI Database and click the name to view its details.
+   ![Database List](./images/database-list.png)
+3. Click **Database Connection**
+   ![DB Connection](./images/database-connection.png)
+4. Click **Download Wallet** to start the download for the client credentials zip file.
+   ![DB Connection Wallet Download](./images/database-connection-download-wallet.png)
+5. When prompted, create and enter a strong password in **Password** and **Confirm password** fields.
+   *(You will use this password to access the wallet when configuring the OAC connection.)*
+6. Click **Download** to save the wallet (.zip) file to your computer.
+   ![Final Wallet Download](./images/database-connection-download-wallet-details.png)
+
+*Keep your downloaded wallet and password safe. You will use these in the next steps to connect OAC to your Autonomous AI Database.*
+
+## Task 2: Create a Database Connection in OAC
+
+1. On the OAC home page, click page menu in the upper left side.
+2. Select **Data**.
+   ![Import template menu](../common/images/analytics-cloud-config-data-connection.png)
+3. Over the imported connection, on the right side, click actions menu and click **Inspect** to view details.
+   ![Select Autonomous AI Database Connection](./images/analytics-cloud-data-connection-inspect.png)
+4. Complete the connection form:
+   * **Connection Name**: Enter a name (e.g., `JMS_AAID_EXPORT`).
+   * **Description**: (Optional) Add a brief description.
+   * **Username**: Enter your database user (e.g., `JMS_EXPORT` or schema user).
+   * **Password**: Enter your database user’s password.
+   * **Client Credentials**: Upload the wallet (.zip) you downloaded earlier.
+   * **Wallet Password**: Enter the password you set when downloading the wallet.
+   * **Service Name**: Select the appropriate TNS alias for your workload (`HIGH`, `LOW`, or `TP`).
+   ![Connection details form](images/analytics-cloud-data-connection.png)
+5. Click **Save** to create the connection.
+
+
+## Task 3: Verify connection to AI Database reloading data
+
+1. Go to Datasets.
+2. Over the imported dataset, on the right side, click actions menu and click **Inspect** to view details.
+   ![Dataset inspection](images/analytics-cloud-dataset-inspect.png)
+3. On the left panel click **Reload Data**.
+4. Click the button **Run Now**.
+   ![Dataset reload data](images/analytics-cloud-dataset-reload-data.png)
+5. The Dataset is queued for reloading and will complete in the background. Click **Close**.
+   ![Dataset close reload_data](images/analytics-cloud-dataset-reload-data-close.png)
+6. On the left panel click **History**. The Status could be **In Queue** or **Running**. 
+   ![Dataset close reload_data](images/analytics-cloud-dataset-reload-data-inqueue.png)
+7. Wait until the execution ends and the status is **Completed**.
+   ![Dataset close reload_data](images/analytics-cloud-dataset-reload-data-completed.png)
+
+## Next Steps
+
+* Use the established connection to create interactive workbooks and dashboards.
+* Explore available Autonomous AI Database tables and columns to design your analytics.
+* Proceed to the next lab to further refine and customize your analytics environment.
+
+Congratulations, you completed the lab! You may now [proceed to the next lab](#next).
+
+## Learn More
+
+* [Connect to Oracle Autonomous AI Transaction Processing](https://docs.oracle.com/en/cloud/paas/analytics-cloud/acsds/connect-oracle-autonomous-transaction-processing.html)
+
+## Acknowledgements
+
+* **Author** - Maria Antonia Merino, Java Management Service
+* **Last Updated By/Date** - Maria Antonia Merino, January 2026

java-management-oac-integration/import-jms-oac-template/import-jms-oac-template.md

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+# Lab 4: Import JMS OAC Template
+
+## Introduction
+
+In this lab, you will connect to your Oracle Analytics Cloud (OAC) environment and import a pre-built analytics workbook template that accelerates your analysis of Java Management Service (JMS) data.
+
+*Estimated Time:* 5 minutes
+
+### Objectives
+
+* Import the provided JMS OAC analytics template.
+
+### Prerequisites
+
+* All previous labs completed, especially [Lab 3: Oracle Analytics Cloud Instance Setup](?lab=oac-instance-setup) (OAC instance, user, and custom role must be set up).
+* Credentials for an OAC user who has the "Author" (or equivalent) application role assigned which enables importing and editing workbooks.
+* Access to the JMS OAC template file (`.DVA` or `.zip`) provided.
+
+## Task 1: Access Your OAC Instance
+
+1. In the Oracle Cloud Console, open the navigation menu, click **Analytics & AI**, then under **AI Data Platform** select **Analytics Cloud**.
+   ![OAC Console Navigation](../common/images/configure-analytics-cloud.png)
+2. On the Analytics Cloud page, select your OAC instance.
+   ![OAC Instance List](../common/images/analytics-instances-list.png)
+3. Under **Access Information**, click the OAC instance URL to launch OAC in your browser.
+   ![OAC URL Access](../common/images/analytics-instance-details.png)
+4. Sign in with the user created and assigned the appropriate role in [Lab 3: Oracle Analytics Cloud Instance Setup](?lab=oac-instance-setup).
+   ![User Account Access](../common/images/user-access.png)
+
+## Task 2: Download the JMS OAC Template
+
+You must download the JMS Data Viewer OAC template to your local computer.
+
+[Download JMS Data Viewer](../common/files/jms_data_viewer.dva)
+
+The JMS Data Viewer (.dva) file provides pre-built dashboards for visualizing Java Management Service data in Oracle Analytics Cloud. Save it in an accessible location to use in the next step.
+
+## Task 3: Import the JMS OAC Workbook Template
+
+1. On the OAC home page, locate and click the **Page Menu** (three dots or lines, usually upper-right).
+2. Select **Import Workbook/Flow**.
+   ![OAC Import Menu](./images/analytics-cloud-import-workbook.png)
+3. Click **Select File**, then locate and select the provided JMS OAC template file (`.DVA` or `.zip`).
+   ![OAC Import Menu](./images/analytics-cloud-import-workbook-select.png)
+4. Click **Import**.
+   ![Select Template File](./images/analytics-cloud-import-workbook-details.png)
+5. When the "Import successful" message appears, click **OK**.
+   ![Select Template File](./images/analytics-cloud-import-workbook-details-ok.png)
+
+## Next Steps
+
+You have now imported the JMS OAC workbook template. You can:
+
+* Update the data connection settings to point to your own Autonomous Database instance or schema.
+
+Congratulations, you completed the lab! You may now [proceed to the next lab](#next).
+
+## Learn More
+
+* [Import, Export, and Share](https://docs.oracle.com/en/cloud/paas/analytics-cloud/acubi/import-export-and-share.html)
+
+## Acknowledgements
+
+* **Author** - Maria Antonia Merino, Java Management Service
+* **Last Updated By/Date** - Maria Antonia Merino, January 2026

java-management-oac-integration/introduction/introduction.md

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+# Introduction
+
+## About Java Management Service and Oracle Analytics
+
+Java Management Service (JMS) is a reporting and management infrastructure integrated with Oracle Cloud Infrastructure Platform services to observe and manage your use of Java SE (on-premise or in the Cloud).
+
+Oracle Analytics Cloud is a scalable and secure Oracle Cloud service that provides a full set of capabilities to explore and perform collaborative analytics for you, your workgroup, and your enterprise.
+
+As a customer, you can:
+* Create interactive workbooks in Oracle Analytics Cloud (OAC) by integrating Java Management Service (JMS) data exports to visualize and track Java SE usage across multiple OCI regions and hybrid environments, including managed instances, Java runtimes, applications, IP addresses, and host names in a centralized view.
+
+
+## About this Workshop
+
+This workshop is a follow up workshop to the [Manage Java Runtimes, Applications and Managed Instances Inventory with Java Management Service](https://livelabs.oracle.com/pls/apex/dbpm/r/livelabs/view-workshop?wid=912) workshop, which we recommend to be completed before beginning this workshop about Integrating Oracle Analytics Cloud with Java Management Service.
+
+This workshop guides you through connecting JMS to Oracle Analytics Cloud, exporting Java inventory and usage data, and building real-time dashboards with data from multiple regions.
+
+*Estimated Time*: 90 minutes
+
+### Objectives
+
+* Understand core concepts of JMS integration with OAC for Java SE monitoring and analytics.
+* Export JMS inventory data to Autonomous AI Database for centralized storage.
+* Provision and connect an OAC instance to Autonomous AI Database for secure data access.
+* Build interactive workbooks and real-time dashboards in OAC using prebuilt templates.
+* Automate periodic data refreshes to maintain up-to-date visualizations of Java usage across regions and hybrid environments.
+
+### Prerequisites
+
+* This workshop requires an Oracle Cloud account. You may use your **own cloud account** or you can get a **Free Trial** account as described in [Get Started](?lab=cloud-login).
+* Have access to the cloud environment with the resources configured by following the steps in the workshop [Manage Java Runtimes, Applications and Managed Instances Inventory with Java Management Service](https://livelabs.oracle.com/pls/apex/dbpm/r/livelabs/view-workshop?wid=912).
+
+## Learn More
+
+* [Java Management Service](https://docs.oracle.com/en-us/iaas/jms/index.html)
+* [Oracle Analytics Cloud](https://docs.oracle.com/en/cloud/paas/analytics-cloud/index.html)
+* [Autonomous AI Database Serverless](https://docs.oracle.com/en-us/iaas/autonomous-database-serverless/index.html)
+* [Oracle University](https://mylearn.oracle.com/ou/home)
+
+
+## Acknowledgements
+
+* **Author** - Maria Antonia Merino, Java Management Service
+* **Last Updated By/Date** - Maria Antonia Merino, January 2026