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| Section | Objectives |
|---|---|
| Topic 1: System Administration | - Instance administration
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| Topic 2: Review and Production | - Document review workflows
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| Topic 3: Data Management | - Object and metadata management
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| Topic 4: Search and Analytics | - Search functionality
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| Topic 5: Workspace Administration | - Workspace creation and configuration
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NEW QUESTION # 28
What production numbering should be used when reproducing documents with the same Bates numbering?
Answer: D
Explanation:
The correct answer is D. Existing production numbering . Relativity's official production set documentation states that Existing production numbering should be selected when you want to re-use the Bates numbering fields from a previously run production set . This is the exact numbering option designed for scenarios where documents are being reproduced but must retain the same Bates values from an earlier production. Relativity further explains that this option is appropriate when you need to change the produced images, produce only a subset of documents from the existing production, or otherwise reissue the same produced documents while preserving the prior numbering.
This aligns directly with re-production workflows. Relativity's re-production documentation also notes that re- production jobs reuse the numbering format and Bates numbers from the original productions , reinforcing that the platform supports maintaining the original numbering scheme instead of assigning new Bates values. That is critical in litigation workflows where Bates continuity must be preserved for references in correspondence, court filings, and prior productions. The other options do not fit this requirement. Page level numbering and document field numbering generate or rely on other numbering methods, while original image numbering is not the production numbering choice used for preserving prior Bates values in a re- production. Therefore, when reproducing documents and keeping the same Bates numbering, the correct production numbering method is Existing production numbering .
NEW QUESTION # 29
With what tool can you rapidly transfer large amounts of data from your RelativityOne storage location to a local computer?
Answer: B
Explanation:
The correct answer is D. RelativityOne Staging Explorer ROSE . Relativity's official documentation states that Staging Explorer enables you to rapidly transfer large amounts of data to and from RelativityOne .
It is specifically intended for high-volume transfer workflows and can be used to download files from your RelativityOne storage location to a local computer . That wording directly matches the question, making ROSE the exact documented tool for this scenario.
This is why the other options are incorrect. Simple File Download is not the primary enterprise-scale utility Relativity documents for rapid bulk transfer from RelativityOne storage. File Transfer Protocol is a generic technology term, not the RelativityOne tool identified by Relativity documentation for this workflow.
Relativity Integration Points RIP is used for moving and integrating data across systems and workspaces, but it is not the official RelativityOne utility described as the mechanism to rapidly move large data volumes between RelativityOne storage and a local machine. Relativity also reinforces ROSE's suitability for large datasets in its best practices and certification materials, which describe it as the tool for high-volume uploads and downloads in RelativityOne environments. From an RCA perspective, this is an important operational distinction because ROSE is purpose-built for staging and large-scale data movement, making it the correct answer.
NEW QUESTION # 30
What filter can you apply to exclude document text before it is analyzed by structured analytics?
Answer: C
Explanation:
The correct answer is D. Regular expression filter. Relativity's Structured Analytics documentation states that a Regular expression filter can be linked to a structured analytics set as an optional setting, and that it is used to clean up extracted text before analysis . The documentation further explains that this setting is implemented through a repeated content filter whose type must be Regular Expression . This directly matches the question's wording about excluding document text before analytics processing begins.
This capability is especially useful when documents contain extraneous content such as dates, URLs, page numbers, Bates numbers, standard disclaimers, or other repeated text that can interfere with email threading or textual near duplicate results. Relativity notes that the filter applies only to the field being analyzed, which is usually Extracted Text unless another field is selected. By removing this noise before the algorithm runs, administrators can improve the quality of structured analytics outcomes.
The other options are not the correct named filter for this function in Relativity's structured analytics workflow. The official setting is specifically the Regular expression filter . Therefore, the correct answer is D
.
NEW QUESTION # 31
After review started, you realize the fixed-length text field you created should have been a long text field.
What is the fastest, most efficient way to populate the new long text field with the values from the fixed- length text field?
Answer: C
Explanation:
The correct answer is D. Use Mass Replace to update the long text field with the fixed-length text field values. Relativity's mass operations documentation explains that Mass Replace can be used not only to replace text with static content, but also for field-to-field operations. Specifically, the official examples include copying the contents of one text field to another and merging the values of a source field with the values of a target field . That directly fits this scenario, where the administrator needs to populate a newly created long text field with the existing values stored in a fixed-length text field across many documents.
The other options are less efficient or not aligned with standard Relativity functionality. Manual updates would be extremely slow and error-prone in an active review. Exporting and then overlaying values would create unnecessary extra steps and administrative overhead. Option B refers to Mass Merge , but in Relativity documentation the Merge mass operation is associated with Analytics entity handling, not with copying document text values between fields. For document field content migration, Mass Replace is the documented bulk-update tool. Because this question focuses on the fastest and most efficient administrative correction after review has started, the best practice is to create the correct long text field and then use Mass Replace to populate it from the original fixed-length text field.
NEW QUESTION # 32
What problem could you identify using the Imaging Warnings tab after imaging a set of documents?
Answer: B
Explanation:
The correct answer is C. Possible cut-off content on imaged MSG or EML files. Relativity's official Imaging Warnings documentation states that the Imaging Warnings object identifies possible cut-off content on imaged MSG or EML files and stores that information. It further explains that users can review these items on the Imaging Warnings tab after imaging completes.
The other choices describe imaging failures or limitations, but they are not what the Imaging Warnings tab is specifically designed to identify. Password-protected failures and general non-imageable content are handled through other imaging or processing error mechanisms. The Imaging Warnings feature is much narrower and is specifically meant to flag the risk that content in imaged MSG or EML items may have been cut off in the rendered output. Therefore, the correct answer is C .
NEW QUESTION # 33
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