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| Section | Objectives |
|---|---|
| Analytics & Review Management | - Structured analytics - Review workflows |
| Case Administration | - Case setup and management - User and group management |
| Workspace Administration | - Workspace configuration - Permissions and security |
| Data Management & Ingestion | - File upload and import workflows - Data loading |
| Productions & Outputs | - Export and reporting - Productions setup |
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NEW QUESTION # 78
What filter can you apply to exclude document text before it is analyzed by structured analytics?
Answer: A
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 # 79
How can you update the Disable On Date field for multiple users?
Answer: B
Explanation:
The correct answer is A. Use a mass operation to update the Disable On Date field. Relativity's Users documentation explicitly states that you can use a mass-operation to set the Disable On Date (UTC) field for multiple users . This is the exact documented method for updating that field across multiple user accounts at once.
The other options are not the documented answer for this workflow. Disabling a group is not the same thing as updating the Disable On Date field on user records. Overlay via Import/Export is not the method Relativity identifies for this task in the Users documentation. Setting the field individually works for a single user, but the question asks specifically about multiple users . Therefore, the correct answer is to use a mass operation to update the Disable On Date field.
NEW QUESTION # 80
What tool can you use to assess the differences within a textual near duplicate group?
Answer: D
Explanation:
The correct answer is A. Relativity Compare . Relativity's official documentation on using near duplicate analysis in review states that the Relativity Compare function can compare two documents to assess their similarities and differences . This is the exact activity described in the question and is directly relevant to working within a textual near duplicate group, where reviewers often need to determine how one member differs from the principal document or from another near duplicate in the set.
The other options do not match that purpose. Image QC is used for image quality control workflows, not for textual comparison of document content. Document View Overlay is not the standard Relativity tool documented for assessing textual differences between near duplicates. Similar Documents View helps surface conceptually or textually related material, but it is not the dedicated side-by-side comparison tool Relativity identifies for evaluating differences. From a Structured Analytics perspective, this distinction matters because near duplicate analysis groups similar records together, but the actual determination of differences between two specific documents is handled through the comparison function. Therefore, when assessing differences within a textual near duplicate group, the correct tool is Relativity Compare .
NEW QUESTION # 81
A client sends you a data set they want processed that is comprised entirely of large Excel files. What is the best Excel Text Extraction Method to get the data to review as quickly as possible?
Answer: A
Explanation:
The correct answer is A. Relativity. Relativity's Processing throughput guidance states that internal performance testing has shown the Relativity text extraction method to be at least two times faster than the native method on Excel, Word, and PowerPoint file types, and also less error-prone than native extraction.
Since the question asks for the best method to get a large Excel-only data set to review as quickly as possible, the documented speed advantage makes Relativity the best answer.
The native-based methods are slower according to that same documentation, even though they may have other use cases. The processing profile documentation also shows that native/failover combinations are available configurations, but the performance guidance specifically favors the Relativity extraction method for speed on Excel files. "Extract and place inline" is not the documented Excel text extraction method choice for this question. Therefore, the fastest and most review-efficient choice for large Excel files is Relativity.
NEW QUESTION # 82
Your document collection contains a subset of invoices that are being identified as textual near duplicates yet are all from different days and are of differing amounts. What setting can you toggle to see if the results can be improved?
Answer: A
Explanation:
The correct answer is A. Ignore Numbers. Relativity's near duplicate documentation explains that when Ignore Numbers is set to true, the similarity calculation considers only tokens beginning with letters, which means numbers are excluded from the similarity percentage calculation. That is directly relevant for invoice populations, because many invoices share nearly identical wording while differing mainly by dates, invoice numbers, quantities, or amounts. In a set like the one described, toggling Ignore Numbers is the setting most likely to change how those documents are grouped and help you assess whether the current near duplicate results can be improved.
The other options do not fit this use case. MD5Hash Verifier is related to hash-based duplicate validation rather than textual near duplicate tuning. Relativity Compare is a review tool for examining differences after grouping, not a setting that changes how the grouping is calculated. Auto-recognize Dates is not the structured analytics tuning option documented for this scenario. Therefore, for invoice-heavy data where numerical differences are driving questionable textual near duplicate results, the correct setting to toggle is Ignore Numbers.
NEW QUESTION # 83
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