Executive Report
Overview
The LightBeam Executive Report provides stakeholders with a comprehensive overview of an organization's sensitive data landscape, compliance status, and potential risks. This document outlines the workflow for generating and interpreting the report, detailing each section and its components.
Generating The Executive Report
To download the Executive Report, follow these steps:
Navigate the Datasources Section within the application.
Within the Datasources section, find and click the "Executive Summary" button to initiate the report generation process.
The system will compile data from all monitored sources and generate the report. Once generated, the Executive Report will be automatically downloaded to your system.
Page-wise Breakdown
3.1 Table of contents
The table of contents lists the main sections of the Executive Report allowing users to quickly navigate.
Overview
Monitored Data Sources
Sensitive Data Detected
Document Classification
Policies Violated
3.2 Overview
The overview page provides a high-level summary of key metrics across all monitored data sources. It Includes:
a. Monitored Data Sources
Total: The overall number of data sources being monitored
At Risk: Number of data sources where policy violations have been detected
b. Sensitive Objects
Total: The overall number of files/tables containing Personally Identifiable Information (PII)
At Risk: Number of sensitive objects with policy violations
c. Sensitive Data Count
Total Found: Overall number of sensitive data instances detected
High Sensitivity: Number of high sensitivity data instances
d. Attributes
Total Found: Overall number of unique attributes identified
High Sensitivity: Number of high sensitivity attributes
Tracking: Total number of attributes being monitored
e. Document Classification
Files: Total number of files analyzed
Classification: Number of distinct document classifications identified
f. Data Subject Categories/Entities
Total: Overall number of data subject categories or entities defined
At Risk: Number of data subject categories/entities with policy violations
g. Policies
Rule Sets: Total number of policy rule sets defined
Rule Set Violated: Number of policy rule sets that have been violated
3.3 Monitored Data Sources
This section provides examples of both structured and unstructured data sources, demonstrating how sensitive data is detected and analyzed across different data types.
Example: MySQL Data Source Review
This page provides a detailed overview of the MySQL data source connected to the LightBeam system.
Key Metrics:
Data Source Name: MySQL review
Connection Status: Connected (indicated by a green label)
Owner's Email: The email address of the data source owner
Databases: The total number of MySQL databases monitored
Tables with PII: The total number of tables containing personally identifiable information
Columns with PII: The total number of columns containing PII
Rule set violated: The number of policy rule sets violated in this data source
Attributes Distribution:
1. All Attributes Donut Chart:
Total count of PII columns for the top 4 attributes
Shows the four most common attributes, ranked by how many columns contain each attribute
Others category for remaining attributes
High Sensitivity Attributes Donut Chart:
Total count of high sensitivity PII columns for the top 4 attributes
Shows the four most common high sensitivity attributes, ranked by how many columns contain each attribute
Others category for remaining high sensitivity attributes
3. Database Distribution Chart:
Total PII tables across all databases
Distribution showing top databases by number of tables containing PII
Percentage breakdown of PII table distribution
Example: Google Drive Data Source Review
This page provides a detailed overview of a Google Drive data source connected to the LightBeam system
Key Metrics:
Data Source Name: fastcomply-drive
Connection Status: Connected (indicated by a green label)
Owner's Email: The email address of the data source owner
Drives: The total number of Google Drive accounts monitored
Files with PII: The total number of files containing personally identifiable information
Attributes: The total number of sensitive data attributes detected
Rule Sets Violated: The number of policy rule sets violated in this data source
Attributes Distribution:
All Attributes Donut Chart:
Total count of attribute instances
Top 5 attributes by frequency of instances
Others category for remaining attributes
High Sensitivity Attributes Donut Chart:
Total count of high sensitivity attribute instances
Top 5 high sensitivity attributes by frequency of instances
Others category for remaining high sensitivity attributes
Document Classification Chart:
Total sensitive objects
Top 5 sensitive document types by frequency
Percentage breakdown of document types
3.4 Sensitive Data Detected
Sensitive Data Attribute Inventory An inventory of all identified sensitive data attributes is presented in a clear and well-organized table format. For each attribute, the following details are provided:
Attribute Name: The label or description assigned to the specific type of sensitive data.
Sensitivity Level: The risk level associated with the attribute, classified as High, Medium, or Low sensitivity.
Total Instances: The total number of instances or occurrences of the attribute detected across all monitored structured sources.
Data Sources Containing Attribute: The number of distinct structured data repositories where instances of the attribute were identified.
3.5 Document Classification
This section presents an overview of the automated document classification analysis conducted on files within the monitored unstructured data sources.
Document type:
The classification process identifies various categories of documents. Key categories include:
Legal Documents: Files related to legal matters, contracts, and agreements.
Human Resource Documents: Employee-related files such as resumes, performance reviews, and employment contracts.
Identity Documents: Files containing personal identification information (e.g., government IDs, passports, driving licenses).
Medical Records: Health-related documents including patient records, prescriptions, and medical reports.
Financial Documents: Files related to financial transactions, tax records, and accounting information.
Unclassified: Files that do not fit into any defined category.
3.6 Policies Violated
This section highlights any instances where the organization's defined data handling policies or security rules were violated within the monitored data sources during the reporting period.
Policy Violation Summary: A clear and concise summary is provided for each policy violation detected, including:
Policy Rule Set Name: The name or identifier of the violated policy or rule set.
Policy Type: The category or area the violated policy falls under (e.g., Access Controls, Data Discovery & Classification).
Affected Data Source(s): The name(s) of the monitored data source(s) where the violation occurred.
Objects Impacted: The number of data objects (e.g., files, database tables) affected by the policy violation.
Entities Impacted: The number of users, individuals, or other entities potentially impacted due to the violation.
3.7 End of Document
This page marks the end of the Executive Report document.
About LightBeam
LightBeam automates Privacy, Security, and AI Governance, so businesses can accelerate their growth in new markets. Leveraging generative AI, LightBeam has rapidly gained customers’ trust by pioneering a unique privacy-centric and automation-first approach to security. Unlike siloed solutions, LightBeam ties together sensitive data cataloging, control, and compliance across structured and unstructured data applications providing 360-visibility, redaction, self-service DSRs, and automated ROPA reporting ensuring ultimate protection against ransomware and accidental exposures while meeting data privacy obligations efficiently. LightBeam is on a mission to create a secure privacy-first world helping customers automate compliance against a patchwork of existing and emerging regulations.
For any questions or suggestions, please get in touch with us at: [email protected]
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