Use Cases Flashcards

1
Q
  1. What is a common active learning use case for legal teams?

a. Prioritized review
b. Language analysis
c. Deduplication
d. Review audio/video data

A

a. Prioritized review

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2
Q
  1. A customer works for a major financial services institution. The institution employs 1,000 traders generating 250,000 communications per day with tools like Bloomberg Chat, Skype, email, and audio files. Which Relativity application can their compliance teams use to continuously and automatically monitor internal and outgoing communications for nefarious activities such as insider trading, collusion, and money laundering?

a. Active learning
b. Relativity Trace
c. Case Dynamics
d. Relativity Legal Hold

A

b. Relativity Trace

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3
Q
  1. Your customer is faced with a second request that requires review of a large amount of documents in a limited amount of time. The case team has little exposure to using analytics solutions and expresses concern about the investment. You recommend a workflow using active learning. What are the benefits to this customer in using active learning? (Select all that apply.)

a. They can bypass review of large amounts of data based on
the engine’s categorization results.
b. They can reduce review hours and related costs.
c. They can provide data to show the effectiveness and
accuracy of the technology to skeptical attorneys.
d. They can preserve custodians’ relevant data.

A

a. They can bypass review of large amounts of data based on
the engine’s categorization results.

b. They can reduce review hours and related costs.

c. They can provide data to show the effectiveness and
accuracy of the technology to skeptical attorneys.

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4
Q
  1. A customer received more than 1.6 million emails across 60
    productions. They had two weeks to cull and review this data.
    They used a Relativity feature to determine that 47% of the
    material didn’t need to be reviewed due to the fact the content wasn’t unique, which saved the end-client an estimated 12,500 hours in review time. What feature did they use?

a. Clustering
b. Relativity Legal Hold
c. Email threading
d. Concept searching

A

c. Email threading

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5
Q
  1. Your customer collected and processed millions of documents on behalf of their client. They will use Relativity Analytics to accelerate their review of the data. What is not a useful way for them to proceed?
    a. Enable clustering to map out groups of conceptually similar
    documents.
    b. Run email threading to identify inclusive emails that can be
    prioritized for immediate review.
    c. Identify highly relevant documents to the case and run
    categorization to pull back other conceptually related
    material.
    d. Use Document Compare to isolate the key differences
    between similar documents.
A

d. Use Document Compare to isolate the key differences
between similar documents.

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6
Q
  1. Document review starts and your customer’s responsibilities
    shift to:
    • Understanding the throughput and accuracy of their
    reviewers.
    • Course correcting when necessary.
    • Providing periodic updates to their client overseeing the
    case.
    What are the best ways for your customer to accomplish this in Relativity? (Select all that apply.)

a. Leverage dashboard capabilities to provide dynamic insight
into how documents are being coded.
b. Use Audit to monitor and run reports on audited user
activity.
c. Ask their reviewers to send them daily reports of their
progress.
d. Install Case Metrics to their instance and run reports with
the application.

A
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7
Q
  1. Relativity Legal Hold is a solution for managing the workflow
    around litigation holds and preservations. It’s also a useful
    solution for any type of activity that requires communicating
    with people, collecting and tracking responses, and reporting.
    What is not a recommended alternative use case for the
    application?
    a. Customer satisfaction surveys.
    b. Data retention schedule management.
    c. Track and review resumes.
    d. Scouting computers for data to be collected.
A

d. Scouting computers for data to be collected.

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