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How to perform a proof of concept for automated discovery using Amazon Macie
- Amazon Macie helps customers identify, discover, monitor, and protect sensitive data stored in Amazon S3.
- Customers need to evaluate and test the capabilities of Macie before using it to meet their data identification and protection goals.
- Macie comes with over 150 managed data identifiers and offers important features such as identifying S3 bucket securities, sensitive data discovery jobs, and automated data discovery.
- Users can define custom data identifiers, stage POC data, run a sensitive data discovery job, review the findings, and enable automated discovery.
- Users can view the individual findings that were generated for each S3 object that was identified as having sensitive data and store and retain sensitive data discovery results to analyze and query later.
- After the POC, evaluate the results to determine how much using Macie can strengthen your organization’s data protection program.
- Planning your POC using the guidance in this post can help you determine more quickly if Macie is a fit for your company.
- AWS customers of various sizes can use Macie to enhance their current data protection strategies and classify and protect the data they store in Amazon S3.
- A successful POC of Macie includes understanding what data Macie can detect and defining custom data identifiers.
- Operationalizing Macie output and refining the managed data identifiers that are required for detecting sensitive data are some of the next steps that other customers have taken after completing their POC with Macie.
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