Question 1

How does BI Validator automate regression testing when migrating from OBIEE 12c to Oracle Analytics Cloud (OAC) or Oracle Analytics Server (OAS)?

Accepted Answer

BI Validator automates regression testing for OBIEE to OAC/OAS migrations by first capturing a baseline snapshot of all OBIEE 12c dashboard and analysis outputs — recording data values, column headers, filter results, and row counts for every analysis in scope. After the RPD and Web Catalog are migrated, BI Validator re-executes the same dashboards in the new environment and compares outputs against the OBIEE 12c baseline. Any analysis returning a different data value, changed column, or missing row in OAC/OAS is flagged as a regression with the specific analysis name, dashboard, OBIEE baseline value, and OAC/OAS actual value — giving the migration team a precise report-by-report view of which analyses were impacted.

Question 2

How does BI Validator compare dashboards and subject areas between OBIEE 12c and OAC/OAS to validate that the migration was successful?

Accepted Answer

BI Validator connects to both the source OBIEE 12c environment and the target OAC or OAS environment simultaneously using Oracle Analytics SOAP services. For dashboard comparison, it executes each dashboard page in both environments side by side and compares data returned in every analysis — flagging any analysis where row count, column values, or filter application differs. For subject area comparison, BI Validator reads metadata from both the OBIEE 12c RPD and the OAC/OAS semantic model, comparing logical columns, hierarchies, aggregation rules, and join definitions to identify any subject area element lost, renamed, or altered during the RPD migration.

Question 3

How does BI Validator validate the functional accuracy of Oracle Analytics analyses by comparing report output against the underlying SQL query?

Accepted Answer

BI Validator runs each Oracle Analytics analysis through the OAC/OAS server to retrieve the actual report output, and simultaneously executes an equivalent SQL query directly against the underlying data source. It then compares the analysis output against the SQL query result row by row and column by column. Any analysis where the displayed value differs from the direct SQL result is flagged as a functional defect — indicating that the RPD semantic layer is applying an incorrect aggregation, join, or expression. This gives Oracle Analytics developers targeted, evidence-based defect reports identifying exactly which analyses contain RPD logic errors requiring correction.

Question 4

How does BI Validator automatically generate and test thousands of adhoc report combinations to validate Oracle Analytics Subject Area design?

Accepted Answer

BI Validator automates Subject Area validation by reading Oracle Analytics metadata and automatically generating thousands of adhoc report combinations — pairing dimensions with measures across different hierarchical levels, applying varied filters, and testing drill-down paths — without any manual test case creation. Each generated combination is executed against the OAC or OAS server and checked for query errors, missing data, duplicate rows, or unexpected NULL values. Any combination producing an error or unexpected result is logged with the specific columns and filters that caused the issue, giving RPD developers a systematic map of Subject Area design problems.

Question 5

How does BI Validator validate Oracle Analytics security settings to confirm that row-level and catalog-level permissions are correctly enforced?

Accepted Answer

BI Validator validates Oracle Analytics security at multiple levels by executing analyses under different user credentials and comparing data returned against the expected security policy. For row-level security, it verifies that users assigned to a specific region or business unit only see data rows for that region. For catalog permissions, it validates that users in a specific role can access only the dashboards and analyses assigned to that role. Any security policy violation — where a user sees data they should not, or cannot access a dashboard they should — is flagged with the specific user, analysis, and the data or permission discrepancy found.

Question 6

How does BI Validator's wizard-based test creation enable bulk creation of hundreds of Oracle Analytics test cases without custom programming?

Accepted Answer

BI Validator's wizard-based test creation reads the OAC or OAS catalog structure and presents a tree view of all dashboards and analyses. Testers create a test suite for an entire workspace by dragging a folder or dashboard group into the test plan — automatically creating a separate test case for every analysis in that folder, including all filter combinations and prompt selections. An embedded browser within BI Validator also allows testers to navigate the live dashboard, make filter and parameter selections interactively, and capture those selections as test case inputs without writing any configuration code — reducing test suite creation from weeks of scripting to hours.

Question 7

How does BI Validator enable enterprise-wide collaboration and centralized result sharing across Oracle Analytics testing teams?

Accepted Answer

BI Validator stores all Oracle Analytics test plans, test case definitions, execution results, and baseline comparison data in a central repository accessible to all team members through a shared web interface. Results are immediately available after each execution — whether triggered manually, scheduled automatically, or kicked off by a CI/CD pipeline — and stored with a full execution history so teams can track whether regressions identified in previous cycles have been resolved. Results can be exported as shareable web reports and distributed to business stakeholders or migration sign-off committees without requiring direct access to the BI Validator interface.

Question 8

How does BI Validator perform performance monitoring of Oracle Analytics dashboards in a production environment?

Accepted Answer

BI Validator's performance monitoring executes configured dashboard and analysis requests against the production OAC or OAS environment on a defined schedule and records end-to-end response times for each dashboard page and analysis. Response times are tracked across runs and visualized in BI Validator's performance dashboard, enabling administrators to identify consistently slow dashboards, detect response time degradation correlated with specific time periods or data volume increases, and establish baseline benchmarks for new deployments. Alerts can be configured to notify administrators when a dashboard's response time exceeds a defined SLA threshold.

Question 9

How does BI Validator conduct stress testing of Oracle Analytics reports to validate performance under concurrent user load?

Accepted Answer

BI Validator's stress testing simulates a configured number of virtual concurrent users each executing the same set of dashboard and analysis requests simultaneously, with stepped load profiles that progressively increase concurrent users from baseline to peak load. The stress test results report average response time, maximum response time, error rate, and query execution duration at each load level — giving Oracle Analytics infrastructure teams the evidence needed to make informed decisions about OAC service capacity sizing, OAS server configuration, or database query optimization before peak-load periods such as month-end financial closes.

Question 10

How does BI Validator integrate with Jenkins or GitLab to enable CI/CD for Oracle Analytics deployments?

Accepted Answer

BI Validator provides both a CLI and a REST API that allow Oracle Analytics test plans to be triggered programmatically from Jenkins, GitLab CI/CD, or any other orchestration tool. When a developer commits a change to the Oracle Analytics environment — such as an RPD modification, catalog reorganization, or new subject area — the CI/CD pipeline invokes the BI Validator CLI or REST API to trigger the configured regression test plan. BI Validator executes tests, compares outputs against the stored baseline, and returns a structured pass/fail result to the pipeline. If any regression is detected, the pipeline is blocked and the developer receives a report identifying exactly which analyses were impacted by the change.

Use Case

Cloud

Analytics

Industry

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Use Case

Cloud

Analytics

Industry

Academy

Support

Oracle Analytics Testing Automation Tool

Benefits of Automating Testing of Oracle Analytics Reports

Better Decisions

Higher Adoption

Cost Reduction

Key Features

Automate Testing of OBIEE to OAC/OAS Migration

Regression testing of Oracle Analytics Dashboards & Analysis

Validate OBIEE 12c to OAS or OAC dashboards Migrations

No code Test Automation for Oracle Analytics

Functional Testing of New OAC/OAS Deployments

Identify differences between Analysis data & SQL output

Test Oracle Analytics Adhoc Reporting & Subject Areas

Test Oracle Analytics Security

Performance & Stress testing of OAC/OAS Reports

Performance testing of Oracle Analytics dashboards

Stress testing of Oracle Analytics dashboards

Easy Wizard-based Oracle Analytics Test Creation

Bulk creation of Oracle Analytics Test Cases

Embedded Browsers to simplify Oracle Analytics Test creation

Enterprise Collaboration amongst Oracle Analytics Testers,Developer,

Enable CI/CD for Oracle Analytics

Integrates with CI/CD tools such as Jenkins & GitLab

Scheduling of Oracle Analytics Tests & Notifications by Email

Other BI Platforms Supported

Case Studies

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Data Quality Monitor

Continuously assess, score, and improve your enterprise data quality using rule-based and AI-powered validation

Automated Data Quality Checks at Scale

AI-Driven Anomaly Detection and Alerts

Low-Code Rule Configuration with Data Rule Wizard

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Generate high-quality synthetic test data securely while maintaining regulatory compliance with HIPAA, GDPR, and CCPA

AI-Powered Synthetic Test Data Generation

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Maximize the efficiency, quality, and reliability of your data pipelines through intelligent automation, validation, and scalability.

100% Data Validation Across Pipelines

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BI Validator

Ensure accuracy, performance, and security of your Business Intelligence dashboards and reports across platforms like Tableau, Power BI, and Oracle Analytics

Automated Regression Testing Across BI Reports

Cross-Platform Validation of Reports and Dashboards

Performance and Load Testing for BI Assets

Access and Security Validation

Aesthetic and Metadata Change Detection

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