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| Section | Objectives |
|---|---|
| Topic 1: System Administration | - Application management
|
| Topic 2: Review and Production | - Document review workflows
|
| Topic 3: Workspace Administration | - Security and permissions
|
| Topic 4: Data Management | - Object and metadata management
|
| Topic 5: Search and Analytics | - Analytics
|
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NEW QUESTION # 47
When using Simple File Upload to import new documents, what determines the Control Number?
Answer: B
Explanation:
The correct answer is C. The name of the file. Relativity's Simple File Upload documentation states that when you upload a document using this feature, Relativity imports metadata including Control Number and File Name. In the Simple File Upload workflow, there is no traditional load file that defines document identifiers the way an Import/Export document load does. The uploaded file itself is the source object for the new document record, and the question's answer choices point to the documented practical behavior that the control number comes from the uploaded file name.
The other options do not align with the Simple File Upload model. ArtifactID is a system-generated identifier, but it does not determine the Control Number. There is no document load file in this workflow, so option B is incorrect. Processing Profile settings belong to Processing workflows, not Simple File Upload, so option D is also incorrect. Relativity's replacement guidance also reinforces the centrality of Control Number in this workflow by stating that you cannot upload a document that shares a Control Number with a document already in Relativity unless you use the replacement workflow. That behavior is consistent with the file name being used to derive the incoming document's control number in Simple File Upload.
NEW QUESTION # 48
You need to create a saved search of all documents containing the term apple that do not contain the term magazine. What dtSearch string would successfully return these documents?
Answer: D
Explanation:
The correct answer is A. NOT magazine AND apple . Relativity's dtSearch syntax documentation confirms that dtSearch supports the Boolean operators AND, OR, and NOT and uses them to connect multiple terms in a single search expression. To return only documents that contain apple while excluding those that contain magazine , the query must require the presence of apple and exclude magazine in the same Boolean expression. Option A does exactly that.
Option B is not correct because Apple NOT magazine is missing the required Boolean connector before NOT
. Relativity's dtSearch guidance and related syntax behavior show that NOT is used as part of a Boolean expression, not as a standalone middle operator without AND or OR. Option C is incorrect because Apple OR NOT magazine would broaden the result set too much, potentially returning documents that do not contain apple at all. Option D is also incorrect because it excludes apple instead of requiring it. Therefore, the valid dtSearch string that successfully returns documents containing apple but not magazine is NOT magazine AND apple .
NEW QUESTION # 49
What tool can you use to assess the differences within a textual near duplicate group?
Answer: A
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 # 50
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: D
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 # 51
What field is set when adding a production data source to a production set?
Answer: D
Explanation:
The correct answer is B. Production type. Relativity's official Production Data Source documentation states that when adding a production data source, one of the fields you configure is Production Type , where you select whether the data source will produce images, natives, or both . This is explicitly part of the production data source setup dialog.
This makes sense because production data sources are used to attach saved searches to a production set and can define how those specific subsets of documents should be produced. Relativity also documents that placeholders can be assigned at the production data source level so that different saved searches in the same production can use different placeholder behavior. However, Production Numbering is defined at the production set level rather than as a field you set when creating the individual production data source.
Likewise, Branding text size and Placeholder image format are production-level settings, not the core field identified in the data source setup described by Relativity.
From an RCA standpoint, this distinction matters because administrators configure overall production behavior in the production set, while more granular document-source behavior is controlled on each production data source. Therefore, the correct answer is B. Production type .
NEW QUESTION # 52
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