最新-信頼的なRCA問題トレーリング試験-試験の準備方法RCA資格模擬

IT業界の一人として、IT領域の現状をよく知っているのでしょう?現在のIT業界でRelativityの資格認証はますます重要になっています。多くの人はRCA試験に悩んでいます。あなたもその中の一員かもしれません。試験に迅速に合格する方法を探していますか?我々のRCA資料を試しましょう。無料のサンプルを提供して、あなたはダウンロードして試すことができます。あなたの要求を満たすなら、弊社のRCA参考書を利用してください。
Relativity RCA Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Topic 1: Data Manipulation and Interaction | 25-30% | - Imaging and Production
- 1. Production setup, staging, and export
- 2. Configure and run imaging jobs
- 3. OCR configuration and processing
- Mass Operations and Tools
- 1. Mass edit, replace, delete, and convert
- 2. Short Message Format (RSMF) handling
- 3. Dashboard and report creation
|
| Topic 2: Data In and Out | 10-15% | - Data Import
- 1. Load file formats and import methods
- 2. Data transfer applications and tools
- Data Export
- 1. Export configurations and load files
- 2. Production and workspace data export
|
| Topic 3: Setup and Management | 30-35% | - Security and Permissions
- 1. Workspace permissions and groups
- 2. Object security and tab visibility
- 3. Instance-level security configuration
- Workspace and Instance Objects
- 1. Configure resource pools and repositories
- 2. Create and configure workspaces
- 3. Manage clients, matters, and users
- Applications and Workflows
- 1. Automated workflows and event handlers
- 2. Audit and system monitoring
- 3. Install, configure, and upgrade applications
|
| Topic 4: Search and Analytics | 20-25% | - Search Capabilities
- 1. Saved searches and search terms reports
- 2. Index creation and maintenance
- 3. Keyword, dtSearch, and Analytics searches
- Structured Analytics and AI
- 1. Structured analytics sets and workflows
- 2. aiR for Review configuration and usage
- 3. Review Center setup and management
|
>> RCA問題トレーリング <<
Relativity RCA認定試験の準備をすれば勉強方法を教える
世界で、多くの人はRCA学習教材を利用しています。ここから見ると、RCA学習教材はいい資料です。彼らはRCA学習教材を勉強したら、RCA試験に合格しました。だから、彼らはRCA学習教材に対して、感謝の気持ちです。つまり、あなたもRCA学習教材を購入すれば、後悔することはありません。
Relativity Certified Administrator 認定 RCA 試験問題 (Q80-Q85):
質問 # 80
How do you move a job to the front of the Branding queue?
- A. Change the job's priority to the lowest value in the queue.
- B. Change the job's submitted date / time.
- C. Cancel and restart the job.
- D. Change the job's priority to the highest value in the queue.
正解:A
解説:
The correct answer is C. Change the job's priority to the lowest value in the queue. Relativity's Branding queue documentation states that only one job runs at a time and the lower numbered job runs first while the higher numbered job runs last. It also explains that you can move jobs by using Change Priority and entering a new integer value. Since lower numbers represent higher queue priority, moving a job to the front means assigning it the lowest priority number among the queued jobs.
This rules out option D, which reverses the queue logic. Changing submitted date/time is not the documented control for moving a branding job forward, and canceling/restarting is unnecessary when Relativity already provides a queue-priority control. Therefore, to move a job to the front of the Branding queue, you change its priority to the lowest value in the queue.
質問 # 81
What tool can you use to assess the differences within a textual near duplicate group?
- A. Relativity Compare
- B. Image QC
- C. Document View Overlay
- D. Similar Documents View
正解:A
解説:
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 .
質問 # 82
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?
- A. Extract and place inline
- B. Native
- C. Native failover to dtSearch
- D. Relativity
正解:D
解説:
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.
質問 # 83
What does the Prepare Only action do on a prioritized review queue?
- A. Runs the saved search and trains the classifier.
- B. Grants reviewers access to the documents in the queue.
- C. Releases checked out documents to idle reviewers so that an active reviewer can code them.
- D. Takes a statistical sample of documents to code first.
正解:A
解説:
The correct answer is B. Runs the saved search and trains the classifier. Relativity's Review Center documentation states that during the Preparing state, the queue is refreshing the saved search for the first time , and for a prioritized review queue , this also trains the classifier . The Review Center admin quick reference guide further states that Prepare Only re-runs the saved search for all queues and retrains the AI classifier for prioritized review queues , and it does not start the queue.
That makes option B the direct documented effect of Prepare Only. It does not grant reviewer access by itself, it does not release checked-out documents, and it is not a statistical sampling action. From a case administration perspective, Prepare Only is used to get the queue ready and refresh the machine-learning state before reviewers begin or resume work. Therefore, the correct answer is B .
質問 # 84
What option cannot be configured when you create a new production data source?
- A. The field to use for production numbering.
- B. The markup set to apply.
- C. The placeholder to apply.
- D. Whether or not to burn redactions on the documents.
正解:A
解説:
The correct answer is A. The field to use for production numbering. Relativity's documentation distinguishes between production set settings and production data source settings . The production set defines overarching settings such as document numbering , appearance of numbering, and related production-wide behaviors. By contrast, the production data source page includes settings such as production type , placeholder image format , burn redactions , burn native redactions , burn PDF redactions , and markup set .
This means the field used for production numbering is not configured at the individual data source level; it belongs to the production set itself. The other options are all part of production data source configuration.
The documentation explicitly shows Burn Redactions and Markup Set , and placeholder behavior is also configured within the production data source settings.
Therefore, the option that cannot be configured when creating a new production data source is the field to use for production numbering , because that is a production-set-level setting rather than a data-source-level one.
質問 # 85
......
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