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<title>OBIEE Testing Archives - Datagaps | Gen AI-Powered Automated Cloud Data Testing</title>
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<title>Testing Automation of OBIEE Subject Areas</title>
<link>https://www.datagaps.com/blog/testing-automation-of-obiee-subject-areas/</link>
<dc:creator><![CDATA[Rajesh Kumar]]></dc:creator>
<pubDate>Mon, 03 Feb 2025 08:28:00 +0000</pubDate>
<category><![CDATA[OBIEE Testing]]></category>
<guid isPermaLink="false">https://staging9.datagaps.com/?p=7330</guid>
<description><![CDATA[<p>From an IT perspective, testing subject areas is fairly complex. Every Subject Area is really a grouping of Dimension Folders (with attributes) and Measures also known as Facts. The dimension folders may have 100s of attributes and connected to fact tables via foreign keys. Typically</p>
<p>The post <a href="https://www.datagaps.com/blog/testing-automation-of-obiee-subject-areas/">Testing Automation of OBIEE Subject Areas</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<p class="font-claude-response-body break-words whitespace-normal">Subject Areas in <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://docs.oracle.com/cd/E53547_01/opera_5_04_03_core_help/OBI_Subject_Areas_and_Data_Cube_Mappings.htm" target="_blank" rel="noopener">Oracle OBI</a></span> simplify ad-hoc analysis for business users, but that flexibility makes them notoriously hard to test — a Subject Area can span multiple dimension folders with hundreds of attributes tied to fact tables. This post explains the Subject Area Test Plan in BI Validator, which automatically generates logical queries across five combination types (dimension-only, fact-only, single dimension-to-fact, multi-dimension-to-single-fact, and multi-dimension-to-multi-fact) to catch ODBC errors and bad joins before business users hit them.</p> </div>
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<p><strong>Key Takeaways</strong></p><ul><li><strong>Combinatorial complexity</strong>: Dimensions with up to 20 attributes, joined to facts via foreign keys, create near-limitless ad-hoc query combinations.</li><li><strong>Two recurring issues</strong>: attribute/fact pairs can trigger ODBC errors, and poorly modeled RPDs can silently insert “CAST AS NULL.”</li><li><strong>Five combination types tested</strong>: dimension-only, fact-only, single dim-to-fact, multi-dim-to-single fact, multi-dim-to-multi-fact.</li><li><strong>Single dim-to-fact = highest coverage</strong>: pairing every attribute with one fact at a time generates the most test volume.</li></ul> </div>
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<h2 class="elementor-heading-title elementor-size-default">Subject Areas in Oracle OBI</h2> </div>
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<p>Subject Areas in <span style="text-decoration: underline; color: #1967d2;"><a class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" style="color: #1967d2; text-decoration: underline;" href="https://docs.oracle.com/cd/E53547_01/opera_5_04_03_core_help/OBI_Subject_Areas_and_Data_Cube_Mappings.htm" target="_blank" rel="noopener">Oracle OBI</a></span> are a business-facing layer that groups dimension attributes and fact measures so business users can build ad hoc analyses without needing to understand the underlying data warehouse. They hide the complexity involved in warehousing projects and present an easy-to-use mechanism to create ad hoc analysis based on the business user’s needs.</p> </div>
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<p>From an IT perspective, <span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/data-testing-concepts/bi-testing-2/" target="_blank" rel="noopener">testing</a></span></span> subject areas is fairly complex. Every Subject Area is really a grouping of Dimension Folders (with attributes) and Measures also known as Facts. The dimension folders may have 100s of attributes and connected to fact tables via foreign keys. Typically, this Star Schema structure is what <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/data-testing-concepts/data-warehouse-testing/" target="_blank" rel="noopener">data warehouse testing</a></span> needs to validate. Engineers, Business Analysts, Quality Assurance teams struggle to ensure that business users do not encounter unpleasant surprises in the form SQL Errors when they try to create and execute analysis from the subject areas.</p> </div>
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<p>To create a new analysis, business users are empowered to pick any subject area, select random combination of dimension attributes and facts as part of the analysis.</p> </div>
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<p>Now, here is the challenge; assume that there 4 dimensions:</p><ul><li>Account</li><li>Leads</li><li>Opportunities</li><li>Time</li></ul> </div>
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<p>Also, assume each dimension has 20 attributes and that “Fact” has referential integrity with all the above dimensions. Now, to address a new Service Request from business, IT has to tweak a few joins. How can subject areas be tested so that enhancements/bug fixes/changes do not cause any regression?</p> </div>
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<p>From our experience, some of the common issues encountered while creating an analysis :</p><p>• A specific combination of attributes and facts may result in ODBC errors.</p><p>• Depending on how the RPD modeled, the physical query may contain ‘CAST AS NULL’ when the BI Server is not able to determine the right way to join tables.</p> </div>
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<p>To catch ODBC errors and unresolved joins like these before they reach business users, <span style="text-decoration: underline; color: #1967d2;"><a class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/bi-testing-tools/bi-validator/" target="_blank" rel="noopener">BI Validator</a></span>‘s Subject Area Test Plan automatically generates logical queries across systematic combinations of dimension attributes and facts, rather than relying on manual, ad hoc spot-checks. The combination types are:</p> </div>
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<th style="padding: 12px; border: 1px solid #ccc;">Query Combination Type</th>
<th style="padding: 12px; border: 1px solid #ccc;">What It Tests</th>
</tr>
</thead>
<tbody>
<tr>
<td style="padding: 12px; border: 1px solid #ccc;">Dimension Attributes Only</td>
<td style="padding: 12px; border: 1px solid #ccc;">Creates one logical query per dimension folder by selecting all attributes within that folder.</td>
</tr>
<tr style="background: #f8f9fa;">
<td style="padding: 12px; border: 1px solid #ccc;">Fact Measures Only</td>
<td style="padding: 12px; border: 1px solid #ccc;">Creates one logical query per fact folder by selecting all measures within that folder.</td>
</tr>
<tr>
<td style="padding: 12px; border: 1px solid #ccc;">Single Dimension to Single Fact</td>
<td style="padding: 12px; border: 1px solid #ccc;">Combines all attributes from a single dimension folder with one fact or measure at a time, typically generating the highest number of logical queries.</td>
</tr>
<tr style="background: #f8f9fa;">
<td style="padding: 12px; border: 1px solid #ccc;">Multiple Dimension to Single Fact</td>
<td style="padding: 12px; border: 1px solid #ccc;">Combines one attribute from each dimension folder with one fact or measure at a time.</td>
</tr>
<tr>
<td style="padding: 12px; border: 1px solid #ccc;">Multiple Dimension to Multiple Fact</td>
<td style="padding: 12px; border: 1px solid #ccc;">Combines one attribute from each dimension folder with all facts or measures in a fact folder.</td>
</tr>
</tbody>
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<p>While these combinations of dimension attributes and facts do not cover all possible combinations, they represent a basic set of tests that can be used to validate the subject area with minimal manual effort.</p> </div>
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<p>We developed this test plan based on decades of experience in the BI space and are really excited about it. Test drive today.</p> </div>
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<h2 id="faq-heading">Frequently Asked Questions: Testing Oracle OBI Subject Areas</h2>
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<summary>1) Why is testing Oracle OBI Subject Areas so complex?</summary>
<p>
Each Subject Area groups multiple dimension folders — potentially with hundreds of attributes — connected
to fact tables via foreign keys in a star schema, so testing every possible business-user query
combination manually isn’t feasible.
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<summary>2) What issues commonly occur when business users query Subject Areas?</summary>
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Two recurring problems are ODBC errors triggered by specific attribute-and-fact combinations, and
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path.
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It’s a test plan that automatically generates logical queries across five combination categories —
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fact, and multiple dimension-to-multiple fact — to validate a Subject Area with minimal manual effort.
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<summary>4) Does the Subject Area Test Plan cover every possible query combination?</summary>
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No — it covers a foundational set of combinations built from Datagaps’ BI testing experience, which
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<p>The post <a href="https://www.datagaps.com/blog/testing-automation-of-obiee-subject-areas/">Testing Automation of OBIEE Subject Areas</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<title>The role of BI Validator in “In-Place” Upgrades</title>
<link>https://www.datagaps.com/blog/the-role-of-bi-validator-in-in-place-upgrades/</link>
<dc:creator><![CDATA[Rajesh Kumar]]></dc:creator>
<pubDate>Tue, 02 Jun 2015 10:36:20 +0000</pubDate>
<category><![CDATA[OBIEE Testing]]></category>
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<description><![CDATA[<p>As most of us in the BI community are aware, In-Place upgrades are fairly common when clients want to go through minor upgrades (e.g OBIEE 11.1.1.7 to 11.1.1.9 or Business Object 4.1 SP5 to 4.1 SP 7). However, there are a number of risks which need to carefully addressed in such scenarios.</p>
<p>The post <a href="https://www.datagaps.com/blog/the-role-of-bi-validator-in-in-place-upgrades/">The role of BI Validator in “In-Place” Upgrades</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<p>In-place upgrades (e.g., OBIEE 11.1.1.7 to 11.1.1.9) carry hidden risks since there’s no reference environment to compare against. Common issues include unnoticed layout changes, logical query errors causing wrong data in charts, undetected security/access problems, and limited testing time before release. BI Validator solves this using its ELV architecture — teams baseline dashboards and reports before the upgrade, then run automated comparisons after, quickly surfacing any regressions in an intuitive, easy-to-understand format.</p> </div>
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<p><strong>Key Takeaways</strong></p><ul><li>No reference environment increases risk — unlike out-of-place upgrades, in-place upgrades lack a parallel environment for comparison, making it hard to confirm dashboards haven’t regressed after updates.</li><li>Layout and logic errors can slip into production — presentation-layer defects (e.g., extra columns) or logical query bugs (e.g., incorrect “count distinct” results) often go unnoticed until users spot them.</li><li>Limited testing windows raise the stakes — compressed timelines for QA and business analysts mean issues like broken access/security permissions may only surface after go-live.</li><li>BI Validator enables baseline-and-compare testing — its ELV architecture lets teams capture a pre-upgrade baseline and run automated post-upgrade comparisons, clearly flagging differences before they impact business users.</li></ul> </div>
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<p>In-place upgrades (e.g., OBIEE 11.1.1.7 to 11.1.1.9) carry hidden risks since there’s no reference environment to compare against. Common issues include unnoticed layout changes, logical query errors causing wrong data in charts, undetected security/access problems, and limited testing time before release. BI Validator solves this using its ELV architecture — teams baseline dashboards and reports before the upgrade, then run automated comparisons after, quickly surfacing any regressions in an intuitive, easy-to-understand format.</p> </div>
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An “in-place” upgrade is a minor version upgrade performed directly on the existing BI environment rather than standing up a new one — common examples include OBIEE 11.1.1.7 to 11.1.1.9 or Business Objects 4.1 SP5 to 4.1 SP7. Because there’s no separate reference environment to compare against, a number of risks need to be carefully addressed in such scenarios. Below are five examples of what can potentially go wrong and how you can leverage <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/bi-testing-tools/bi-validator/" target="_blank" rel="noopener">BI Validator</a></span> to validate “in-place” upgrades.
<ol>
<li>Because there’s no separate reference environment (unlike an “out-of-place” upgrade), comparing dashboards, reports, and performance before and after the upgrade becomes challenging. For example, with 50 dashboards carrying extensive customization, confidently confirming none of them have regressed after an upgrade from OBIEE 11.1.1.7 to 11.1.1.9 is difficult without a systematic baseline.</li>
<li>Often, defects or regression in the Presentation Server module in the newer version of OBI may accidentally change the layout of the reports. For example OBIEE 11.1.1.7 to 11.1.1.9 caused an extra column to be added in the table view. In our experience, such issues slip through the cracks and and go into production, completely unnoticed. This could be minor but will leave a negative impression on the business user’s mind.</li>
<li>In few cases, a minor upgrade may have an unintended impact on logical queries and that could result in unwarranted data differences in the upgraded environment. For example, in OBIEE 11.1.1.9, if you exclude a measure column with “count distinct”, the chart shows wrong data. It works find in the edit mode but shows wrong numbers when we run it.</li>
<li>While in-place upgrades are inherently risky, the time allocated for Business Analysts, Quality Analysts and Testing Teams is relatively less and they may not be able to go through complete testing cycles. As an example, security and <span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/compliance-solutions/" target="_blank" rel="noopener">access compliance</a></span></span> issues could go undetected until a business user files a service request indicating that they do not have access to a specific report in production.</li>
<li>Since the production will also be upgraded, there is a need for running a quick set of regression tests before releasing the environment to the users. However, business cannot afford the long down times generally needed for validating the environment manually post upgrade.</li>
</ol>
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<tr style="background: #d6e3f5;">
<th style="padding: 12px; border: 1px solid #ccc;">#</th>
<th style="padding: 12px; border: 1px solid #ccc;">Risk</th>
<th style="padding: 12px; border: 1px solid #ccc;">What Can Go Wrong</th>
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<td style="padding: 12px; border: 1px solid #ccc;">1</td>
<td style="padding: 12px; border: 1px solid #ccc;">No reference environment</td>
<td style="padding: 12px; border: 1px solid #ccc;">Comparing dashboards, reports, and performance is hard without a baseline to check against</td>
</tr>
<tr style="background: #f8f9fa;">
<td style="padding: 12px; border: 1px solid #ccc;">2</td>
<td style="padding: 12px; border: 1px solid #ccc;">Presentation Server regressions</td>
<td style="padding: 12px; border: 1px solid #ccc;">Layout changes (e.g., an extra table column) can slip into production unnoticed</td>
</tr>
<tr>
<td style="padding: 12px; border: 1px solid #ccc;">3</td>
<td style="padding: 12px; border: 1px solid #ccc;">Logical query impact</td>
<td style="padding: 12px; border: 1px solid #ccc;">Minor upgrades can silently change query behavior (e.g., “count distinct” measures returning wrong data)</td>
</tr>
<tr style="background: #f8f9fa;">
<td style="padding: 12px; border: 1px solid #ccc;">4</td>
<td style="padding: 12px; border: 1px solid #ccc;">Compressed testing timelines</td>
<td style="padding: 12px; border: 1px solid #ccc;">Limited time for QA can let issues like security/access misconfigurations go undetected until users report them</td>
</tr>
<tr>
<td style="padding: 12px; border: 1px solid #ccc;">5</td>
<td style="padding: 12px; border: 1px solid #ccc;">Limited downtime for validation</td>
<td style="padding: 12px; border: 1px solid #ccc;">Production upgrades need fast regression testing, but manual validation takes longer than the business can afford</td>
</tr>
</tbody>
</table>
Now, how can BI Validator help in the above situations?
BI Validator makes testing the above scenarios amazingly easy for you. Using our patented ELV architecture, you can baseline your dashboards and reports prior to the upgrade using simple user interfaces and then, run the tests after the upgrade. BI Validator presents any differences in a very intuitive manner so that the user can understand the exact differences and act accordingly.
Stay tuned to know how <a href="https://www.datagaps.com/bi-testing-tools/bi-validator/"><span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;">BI Validator</span></span></a> can help during an “Out-of-place” Upgrade:
Try <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/request-a-demo/" target="_blank" rel="noopener">BI Validator</a></span> today. It hardly takes 5 minutes to get up and running. </div>
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<h2>FAQs: In-Place BI Upgrades</h2>
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<details>
<summary>1) Why are in-place BI upgrades risky compared to out-of-place upgrades?</summary>
<p>
In-place upgrades do not provide a separate reference environment for comparison. As a result, teams cannot easily verify that dashboards and reports continue to function correctly after the upgrade, making issues detectable only through testing of the upgraded production environment.
</p>
</details>
<details>
<summary>2) What kinds of problems commonly go unnoticed after an in-place upgrade?</summary>
<p>
Common issues include dashboard and report layout changes such as missing or extra columns, query logic errors that generate incorrect metrics or visualizations, and broken security or access permissions that prevent users from viewing reports.
</p>
</details>
<details>
<summary>3) How does limited testing time affect upgrade quality?</summary>
<p>
Compressed QA and business validation timelines often leave insufficient time to manually verify every dashboard and report. This increases the likelihood that subtle issues, including data discrepancies and access problems, remain undetected until after deployment.
</p>
</details>
<details>
<summary>4) How does BI Validator help reduce risk during in-place upgrades?</summary>
<p>
BI Validator automates regression testing by comparing reports, dashboards, KPIs, filters, security settings, and underlying data before and after the upgrade. This helps teams quickly identify changes, validate upgrade quality, and reduce the risk of production issues.
</p>
</details>
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<p>The post <a href="https://www.datagaps.com/blog/the-role-of-bi-validator-in-in-place-upgrades/">The role of BI Validator in “In-Place” Upgrades</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
]]></content:encoded>
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<item>
<title>BIWA SIG 2014</title>
<link>https://www.datagaps.com/blog/biwa-sig-2014/</link>
<dc:creator><![CDATA[Rajesh Kumar]]></dc:creator>
<pubDate>Thu, 30 Jan 2014 10:58:45 +0000</pubDate>
<category><![CDATA[OBIEE Testing]]></category>
<guid isPermaLink="false">https://staging9.datagaps.com/?p=7128</guid>
<description><![CDATA[<p>Balaji Yelamanchili shared the latest and greatest from Oracle. It was nice to know that Oracle is investing in improving the user experience of the BI Platform & Applications and enhancing support for mobile platform. I saw a demo of Endeca for the first time and I should say that it is pretty cool!</p>
<p>The post <a href="https://www.datagaps.com/blog/biwa-sig-2014/">BIWA SIG 2014</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
]]></description>
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<p>I pulled the full content, but I want to flag something before drafting: this is a very short, event-recap post from January 2014 about attending the BIWA SIG conference — it’s mostly a few paragraphs of informal commentary (a demo of Oracle Endeca, general impressions of the event, low attendance) with no real technical or product substance. There isn’t much “meat” here to extract into AEO-style structured content, and it’s now 12 years out of date (references a “next BIWA SIG” from January 2015).</p> </div>
</div>
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<p><strong>Key Takeaways</strong></p><ul><li class="font-claude-response-body whitespace-normal break-words pl-2"><strong>Datagaps sponsored and attended BIWA SIG 2014</strong>, a BI-focused event in Redwood City, CA, as part of its ongoing event circuit.</li><li class="font-claude-response-body whitespace-normal break-words pl-2"><strong>Oracle previewed BI Platform investments</strong>, including improved user experience and expanded mobile support, alongside a first demo of Oracle Endeca’s UI.</li><li class="font-claude-response-body whitespace-normal break-words pl-2"><strong>Datagaps received positive market feedback</strong> on its solution portfolio from bloggers, potential clients, and partners at the event.</li><li class="font-claude-response-body whitespace-normal break-words pl-2"><strong>Attendance was a noted weak point</strong>, with few actual customers present beyond Oracle staff and partners — prompting plans to improve outreach for future events.</li></ul> </div>
</div>
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<p>We just came back last night from <span style="color: #1967d2;"><a style="color: #1967d2;" href="https://www.linkedin.com/company/biwa-sig" target="_blank" rel="noopener"><span style="text-decoration: underline;">BIWA SIG</span></a></span>, a BI related event that was held in Redwood City, CA. The organizers did a great job of putting together wonderful sessions spanning all areas of Analytics.</p><p>Balaji Yelamanchili shared the latest and greatest from Oracle. It was nice to know that Oracle is investing in improving the user experience of the BI Platform & Applications and enhancing support for mobile platform. I saw a demo of Endeca for the first time and I should say that it is pretty cool! Not sure about the underlying algorithms and how well does it interpret unstructured text but the UI is awesome!</p><p>On our solution portfolio, we got very positive feedback from few bloggers, potential clients and partners and that is always encouraging.</p><p><a href="https://www.linkedin.com/company/biwa-sig" target="_blank" rel="noopener"><span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;">BIWA SIG</span></span></a> is definitely part of our yearly event circuit now. We sponsored the event last year, this year and most likely will do so next year as well. The only thing that disappointed us was the attendance. Other than Oracle folks and partners, there were very few customers. Hopefully next year, we will better collaborate with the organizers and help them spread the work so that more folks can benefit from this extremely focused and well organized event!</p> </div>
</div>
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<h2 class="elementor-heading-title elementor-size-default">Next BIWA SIG:</h2> </div>
</div>
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<p><strong style="color: #000000;">When:</strong><span style="color: #000000;"> January 27th – 29th of 2015. Visit </span><a style="background-color: #fafafa;" href="https://www.linkedin.com/company/biwa-sig" target="_blank" rel="noopener"><u>http://www.biwasummit.com</u> </a><span style="color: #000000;"> for further updates.</span></p><h6><strong>Where:</strong> Oracle Conference Center, Redwood City, CA</h6> </div>
</div>
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<img loading="lazy" decoding="async" width="640" height="640" src="https://www.datagaps.com/wp-content/uploads/BIWA-SIG-2014-19.svg" class="attachment-large size-large wp-image-7131" alt="BIWA-SIG-2014-19" /> </div>
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<h2 class="elementor-heading-title elementor-size-default">About Datagaps:</h2> </div>
</div>
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<p>Our vision is empowering our customers with trustworthy Business Intelligence and Data.</p> </div>
</div>
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<h2 class="elementor-heading-title elementor-size-default">Who We Are:</h2> </div>
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<h2 class="elementor-heading-title elementor-size-default"><span>Trusted Globally by more than 70 Companies for Data Test Automation Solutions</span></h2> </div>
</div>
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<p><a href="http://datagaps.com"><span style="text-decoration: underline;">Datagaps</span> </a>is passionate about data-driven testing automation. Our flagship solutions, ETL Validator, Data Flow & BI Validator are designed to help customers automate the testing of ETL, BI, Database, Data Lake, Flat File, XML Data Sources. Our tools support Snowflake, Tableau, Amazon Redshift, Oracle Analytics, Salesforce, Microsoft Power BI, Azure Synapse, SAP BusinessObjects, IBM Cognos etc. data warehousing projects and BI platforms.</p> </div>
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<h2 class="elementor-heading-title elementor-size-default">Mission Statement:</h2> </div>
</div>
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<p><span style="text-decoration: underline;"><a href="http://datagaps.com/">Datagaps </a></span>was started in the year 2010 with the mission of building trust in enterprise data and reports. We provide software for ETL Data Automation, Data Synchronization, Data Quality, Data Transformation, Test Data Generation, and BI Test Automation. <span style="text-decoration: underline;"><a href="https://www.datagaps.com/">Datagaps</a></span> is an innovative company focused on providing the highest customer satisfaction.</p> </div>
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<h2 id="faq-heading">FAQs: BIWA SIG 2014</h2>
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<details>
<summary>1) What was BIWA SIG 2014?</summary>
<p>
BIWA SIG 2014 was a Business Intelligence-focused conference held in Redwood City,
California, centered on Oracle’s Analytics ecosystem, which Datagaps attended as
both a participant and sponsor.
</p>
</details>
<details>
<summary>2) What Oracle updates were shared at BIWA SIG 2014?</summary>
<p>
Oracle shared plans to continue investing in its BI Platform through user experience
enhancements, expanded mobile capabilities, and an early preview of the Oracle
Endeca user interface.
</p>
</details>
<details>
<summary>3) How was Datagaps’ presence received at the event?</summary>
<p>
Datagaps received positive feedback on its solution portfolio from bloggers,
prospective customers, and partners who attended the conference.
</p>
</details>
<details>
<summary>4) Did Datagaps plan to continue participating in BIWA SIG?</summary>
<p>
Yes. Although customer attendance at the 2014 event was lower than expected,
Datagaps expressed its intention to continue sponsoring and participating in
future BIWA SIG conferences.
</p>
</details>
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<p>The post <a href="https://www.datagaps.com/blog/biwa-sig-2014/">BIWA SIG 2014</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<title>OBI Dashboard Regression Testing</title>
<link>https://www.datagaps.com/blog/obi-dashboard-regression-testing/</link>
<dc:creator><![CDATA[Rajesh Kumar]]></dc:creator>
<pubDate>Thu, 02 May 2013 10:42:01 +0000</pubDate>
<category><![CDATA[OBIEE Testing]]></category>
<guid isPermaLink="false">https://staging9.datagaps.com/?p=7140</guid>
<description><![CDATA[<p>Assume that you have 250 dashboards which are widely used by your marketing, sales, finance and other divisions within your enterprise. So far, things have been running well but the current version of your ETL Tool will not be supported from the July 1st 2013, which is 45 days away and there</p>
<p>The post <a href="https://www.datagaps.com/blog/obi-dashboard-regression-testing/">OBI Dashboard Regression Testing</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
]]></description>
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<p><span data-teams="true">This post illustrates <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/bi-testing-tools/" target="_blank" rel="noopener">BI Validator’s</a></span> use for regression testing dashboards during <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/data-validation-etl-testing-tools/" target="_blank" rel="noopener">ETL tool</a></span> upgrades, using a scenario of 250 enterprise dashboards needing validation within a tight 45-day migration window. BI Validator lets teams benchmark dashboards before an upgrade and automatically compare them afterward, intuitively flagging any differences. This eliminates manual, error-prone methods like printing dashboards for comparison or switching between browser environments, helping IT teams minimize risk and effort during time-constrained ETL or platform upgrades.</span></p> </div>
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<p><strong>Key Takeaways</strong></p>
<ul>
<li><strong>BI Validator enables pre/post-upgrade benchmarking</strong> — dashboards are captured before an ETL or platform upgrade, then automatically compared afterward to detect any unintended changes.</li>
<li><strong>Built for time-constrained upgrade scenarios</strong> — the example illustrates a realistic case: 250 dashboards needing validation within a 45-day window due to a mandatory ETL tool upgrade.</li>
<li><strong>Replaces manual, error-prone comparison methods</strong> — teams previously relied on printing dashboards or manually switching between browser environments to spot differences, both slow and unreliable at scale.</li>
<li><strong>Differences are displayed intuitively</strong> — BI Validator highlights discrepancies in a way that’s easy for users to understand and act on, without deep technical interpretation.</li>
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<p class="wp-block-paragraph">BI Validator can automate <a class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" href="https://www.datagaps.com/data-testing-concepts/bi-testing-2/" target="_blank" rel="noopener"><span style="text-decoration: underline; color: #1967d2;">regression testing</span></a> of dashboards — comparing them before and after a change to catch any differences a manual review might miss. Below is a simple and real example of that in action.</p>
<p class="wp-block-paragraph">Assume that you have 250 dashboards which are widely used by your marketing, sales, finance and other divisions within your enterprise. So far, things have been running well but the current version of your ETL Tool will not be supported from the July 1st 2013, which is 45 days away and there is no option for you but to upgrade from 8.x to 9.x in this timeframe. Sounds familiar? 🙂</p>
<p class="wp-block-paragraph">The IT team is now under tremendous pressure to do the upgrade in a very short period of time and yet, ensure that the process has no negative implications on the dashboards and reports used in the enterprise.</p>
<p class="wp-block-paragraph">Given that there is no big budget and not much time left, what is the best way to solve this problem?</p>
<p class="wp-block-paragraph"> IT teams can use BI Validator to benchmark all 250 dashboards prior to the <a class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" href="https://www.datagaps.com/etl-testing-tools/etl-validator/" target="_blank" rel="noopener"><span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;">ETL tool</span></span></a> upgrade, then compare them against the same dashboards after the upgrade. Any differences BI Validator finds are displayed in an intuitive way that’s easy for the user to understand and act on. Below is an example –</p>
<p class="wp-block-paragraph"><span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/bi-testing-tools/bi-validator/">BI Validator</a> </span></span>thus eliminates two common testing paradigms to identify differences between dashboards.</p>
<ul class="wp-block-list">
<li>Printing dashboards and manually comparing them.</li>
<li>Switching between multiple environments in a browser and manually comparing them.</li>
</ul>
<p><strong>Key takeaway:</strong> whether the trigger is a forced ETL upgrade deadline or a routine platform change, comparing 250 dashboards by hand — printing them out or flipping between browser tabs — simply doesn’t scale under a tight timeline. Automating that comparison is what turns a high-risk, all-hands upgrade into a manageable, low-drama one.</p>
<p class="wp-block-paragraph">In addition to the above, you can run a number of other tests as well to quickly validate and minimize the risk involved with upgrades and other under the hood changes. We care about usability and made this tool incredibly easy to use! <span style="text-decoration: underline;"><span style="color: #1967d2; text-decoration: underline;"><a style="color: #1967d2; text-decoration: underline;" href="https://www.datagaps.com/request-a-demo/" target="_blank" rel="noopener">See it yourself!</a></span></span></p>
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When an ETL tool is upgraded, dashboards built on top of it can be affected in unexpected ways —
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<p>The post <a href="https://www.datagaps.com/blog/obi-dashboard-regression-testing/">OBI Dashboard Regression Testing</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<title>OBIEE 11g upgrade : Fixing consistency check errors during RPD Upgrade</title>
<link>https://www.datagaps.com/blog/obiee-11g-upgrade-fixing-consistency-check-errors-during-rpd-upgrade/</link>
<dc:creator><![CDATA[Rajesh Kumar]]></dc:creator>
<pubDate>Sat, 02 Feb 2013 10:47:45 +0000</pubDate>
<category><![CDATA[OBIEE Testing]]></category>
<guid isPermaLink="false">https://staging9.datagaps.com/?p=7143</guid>
<description><![CDATA[<p>This article walks you through the consistency check warnings found in the BI Apps RPD after running the 11.1.1.7 upgrade assistant on an 10.1.3.4.1 RPD.</p>
<p>The post <a href="https://www.datagaps.com/blog/obiee-11g-upgrade-fixing-consistency-check-errors-during-rpd-upgrade/">OBIEE 11g upgrade : Fixing consistency check errors during RPD Upgrade</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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<p>This troubleshooting guide addresses 9 common consistency check warnings encountered when upgrading OBIEE RPDs from 10.1.3.4.1 to 11.1.1.7 using the Upgrade Assistant. It covers specific warning codes — including 39003 (missing functional dependency), 38028 (invalid data type), 39057 (unused physical table mappings), 39009 (aggregate source join errors), and more — explaining their root causes, typically tied to disabled Logical Table Sources or misaligned aggregation levels, and provides step-by-step solutions for each.</p> </div>
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<p><strong>Key Takeaways</strong></p><ul><li>Disabled Logical Table Sources cause cascading warnings — unused LTS from the 10g RPD get disabled during upgrade, directly triggering warnings 39003 and 38028; cleaning these up beforehand can prevent both.</li><li>Aggregation level mismatches drive multiple errors — warnings 39009 and 39074 stem from fact and dimension tables having misaligned aggregation content levels (e.g., “Detail” vs. a higher level), requiring content tab updates to align grains.</li><li>Missing physical joins are a recurring root cause — warnings 39008 and 39009 both point to missing or incorrect joins between Logical Table Sources and fact tables in the physical layer.</li><li>Some warnings need manual reconfiguration, not just cleanup — issues like 39062 (wrong connection pool in init blocks) and 39076 (disabled “Use for Display” property) require explicit manual fixes rather than pre-upgrade prevention.</li></ul> </div>
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<p>This article walks you through the consistency check warnings found in the BI Apps RPD after running the 11.1.1.7 upgrade assistant on an <span style="text-decoration: underline; color: #1967d2;"><a style="color: #1967d2; text-decoration: underline;" href="https://docs.oracle.com/cd/E63231_01/doc/BIAUP/GUID-B34D1BC8-1806-4B5D-B7F1-C5D1F3842549.htm">10.1.3.4.1 RPD.</a></span></p> </div>
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<ol><li><strong>Warning [39003]</strong>– Missing functional dependency association of a column.<br />Any Logical Table Source that has been unused in 10g is disabled during the upgrade. Cleaning up such tables before the upgrade might help avoid this warning.<br /><strong>Solution: </strong>Enable all the Logical Table Sources that are disabled during the upgrade.</li></ol> </div>
</div>
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<div class="elementor-widget-container">
<ol><li><strong>Warning [38028]</strong>– column does not have valid data type. I encountered this error because of the disabled Logical Table Sources (from warning 39003). The datatype for all the columns belonging to the disabled LTS were set to null.<br /><strong>Solution: </strong>Fixing the warning 39003 should fix this error, otherwise check to see if the column has a valid datatype.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39057]</strong>–There are physical tables mapped in Logical Table Sources that are not used in any column mappings or expressions.<br /><strong>Solution: </strong>The recommendations to workaround this issue:</li></ol> </div>
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<ol><li>Delete the unused logical tables. Delete the aggregations set for that dimension in the content tab of the fact.</li><li>Create dummy mapping columns from that table.</li></ol> </div>
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<p><strong>Metalink note: Warning 39057 [ID 1386095.1]</strong><br />Cleaning up any unused logical tables pre upgrade, might help from running into this warnings.</p> </div>
</div>
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<ol><li><strong>Warning [39009]</strong>– Logical fact table FACTS have an aggregate source that does not join to a Dimension: source at the proper level of detail.<br /><strong>Solution: </strong>Make sure there is a physical join between the fact Logical Table Source and dimension’s Logical Table Source. Make sure the aggregation levels are set at the same grain for both dimension and fact on the content tab.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39076]</strong>– Logical level does not have any key with Use for Display property on.<br />‘Use for Display’ option is turned off during the upgrade.<br /><strong>Solution: </strong>Turn on the ‘Use for Display’ option for all the keys specified.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39008]</strong>– Logical dimension table has a source that does not join to any fact source.<br />The Logical levels on the content tab for LTS and Fact table are not set properly.<br />The join between the LTS and Fact table is missing in the physical layer.<br /><br /><strong>Solution: </strong>Fix the Logical levels on the content tab for Logical Table Sources and Fact table. Both should be set to the same Aggregation level. Check for any missing foreign key joins between LTS and Fact table in physical layer.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39062]</strong>– Initialization block uses Connection Pool which is used for report queries. This may impact query performance. <br /><strong>Solution: </strong>Update the initialization blocks to use the right connection pool. If a connection pool for the init block does not exist, create a new connection pool so that it does not use the connection pool specified for the queries.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39028]</strong>– The features in database does not match the defaults. This may cause query problems. <br /><strong>Solution: </strong>Make sure all the required database features are turned on.</li></ol> </div>
</div>
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<ol><li><strong>Warning [39074]</strong>– Logical dimension table has a source with aggregation content set to level ‘Detail’. The same dimension has aggregation content set in fact source to a higher level. <br /><strong>Solution: </strong>The aggregation levels are set at different grain for fact dimension tables. Update the content tab for dimension and fact to be at the same level.</li></ol> </div>
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<h2 id="faq-heading">FAQs: OBIEE RPD Upgrade Warnings</h2>
<section class="faq-section" aria-labelledby="faq-heading">
<div class="faq-list">
<details>
<summary>1) What causes warning 39003 (“could not compute a functional dependency”) during OBIEE RPD upgrade?</summary>
<p>
This warning typically occurs when a Logical Table Source (LTS) is disabled during
the upgrade because it was unused in the original 10g RPD. Removing or cleaning up
these disabled LTS objects before upgrading usually resolves the issue.
</p>
</details>
<details>
<summary>2) How do you fix warning 38028 (“invalid data type”) in the Business Model layer?</summary>
<p>
Warning 38028 is commonly caused by the same disabled Logical Table Source (LTS)
issue that triggers warning 39003. Reviewing and removing unused or disabled LTS
mappings typically resolves both warnings together.
</p>
</details>
<details>
<summary>3) Why does warning 39009 (“no fact source contains all mapped dimensions”) appear?</summary>
<p>
This warning usually indicates a mismatch in aggregation content levels between
fact and dimension tables or a missing physical join between the Logical Table
Source (LTS) and the fact table. Correcting the content levels and physical joins
resolves the warning.
</p>
</details>
<details>
<summary>4) What causes warning 39062 during an RPD upgrade?</summary>
<p>
Warning 39062 occurs when an initialization block references an incorrect
connection pool. Unlike some upgrade warnings, it requires a manual update to
the initialization block’s connection pool configuration after the upgrade.
</p>
</details>
<details>
<summary>5) How do you resolve warning 39076 related to the “Use for Display” property?</summary>
<p>
This warning appears when the <strong>Use for Display</strong> property is disabled
for a column that requires it. Re-enabling this property for the affected column
resolves the warning.
</p>
</details>
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<p>The post <a href="https://www.datagaps.com/blog/obiee-11g-upgrade-fixing-consistency-check-errors-during-rpd-upgrade/">OBIEE 11g upgrade : Fixing consistency check errors during RPD Upgrade</a> appeared first on <a href="https://www.datagaps.com">Datagaps | Gen AI-Powered Automated Cloud Data Testing</a>.</p>
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