Reduce cost and mitigate risk with sophisticated content analysis, data identification, and secure data transfer in a highly automated and scalable solution.

The FileFacets Platform

FileFacets is an online privacy compliance and enterprise analytics platform that makes it easy for businesses to locate and process unstructured content from multiple sources across the enterprise to protect sensitive data and mitigate risk.

The platform enables organizations to perform sophisticated data discovery and advanced content search of networks, servers, desktops and laptops, identifying to protect sensitive corporate information and Personally Identifiable Information (PII), removing Redundant, Obsolete and Trivial data (ROT) and facilitating the secure transfer of data between repositories.

Hybrid-Cloud Architecture

A software agent is installed on a virtual machine in the enterprise environment, while the FileFacets platform is accessed through a web browser. All source content remains where it is in its native repositories – no content is copied to the cloud – ensuring all corporate and sensitive data remains secure.

Full Text Searching

FileFacets scans all documents to create a full text index by where users can use regular expression searching by pattern or keywords to find exactly what they are looking for – or to discover content they didn’t know they had – across file shares, ECMs, email or desktops.

Dynamic Clustering

Keep related data together with FileFacets‘ dynamic clustering.

The user can build a model that will create clusters based on subject matter, such as grouping all data containing PII such as drivers licenses or health information.

Machine Learning Classification

FileFacets learns from previous decisions you’ve made when classifying data.

As you classify documents, FIleFacets picks up on your tendencies and makes it easier to classify records based on a user’s clustering habits.

FileFacets searches multiple network and cloud-based environments

File Sharing Environments

FileFacets searches for and aggregates PII from unstructured network-based and cloud-based file sharing repositories.

Enterprise Content Management Systems

FileFacets partners with leading ECM technology platforms, allowing users to search for and aggregate PII from multiple systems.

Microsoft Exchange Servers

FileFacets allows users to discover and action what sensitive information is being stored in Exchange.

Individual Desktops

FileFacets searches enterprise desktops for PII and allows users to partition what is personal content vs. what is corporate content.


Dashboard

Locate and view content across the entire enterprise.

Use Cases

  • Content analytics
  • Enterprise inventory & indexing
  • Enterprise business analysis and strategic planning
  • Retention/Disposition Design
  • MSP Sales tool
  • POI Sales tool
  • Deeper dive ROT analysis
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Select Sources: The source repository is the location of the files being scanned and indexed.

  • Select from multiple source repositories
  • Add new sources to scan
  • See previously added sources
  • Immediately scan sources, or schedule a scan for a later time

 

Dashboard: The analytics displayed present a summary of all source repositories added within a Dashboard project.

  • Review metrics corresponding to repositories scanned bases on criteria such as age, size, and file type
  • Provides users with a breakdown on any Personally Identifiable Information that is present within their data
  • Each dashboard can be viewed as a downloadable report


File Cleanup

Most file repositories contain a large number of files without any valid business value. These may include redundant, obsolete, or trivial (ROT) files. In this phase, users can create rules to identify ROT files and action them appropriately. These files can cause your structure to become increasingly difficult to manage and can clog the system. FileFacets File Cleanup Module makes it easy for you to find and manage ROT.

Use Cases

  • ROT cleanup
  • Deduplication
  • Server Decommissioning
  • Workforce Restructuring
  • Legal Hold
  • Legal Liability Policy
  • Repository alignment and comparison
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Select Sources: The source repository is the location of the files being scanned and indexed. This could include Shared Drives, ECMs, Microsoft Exchange Servers, and Individual Desktops

  • Select from multiple source repositories
  • Add new sources to scan
  • See previously added sources
  • Immediately scan sources, or schedule a scan for a later time

 

Select Target System: The target system is where you would like to move your files to after completing a project. This could include Shared Drives, ECMs, Microsoft Exchange Servers, and Individual Desktops.

  • Select from multiple target repositories

 

Define Target Tree: Build out the Target structure with metadata groups.

  • Build a folder structure that represents the organizational configuration in the destination target system
  • Create metadata groups and apply to the folder structure in the target tree

 

Duplicates: Identify duplicates to reduce files

  • MD5 Checksum code (Byte to Byte comparison of each file) is done during the scan.
  • The code is calculated by comparing everything in the file contents
  • While none of the content is stored with FileFacets, the code allows the tool to report on exact duplicates
  • Flag files as duplicates so that they will not be mapped to the target tree and so that they can be actioned appropriately

 

Define Pattern Search: create groups of expressions to extract and analyze values from the data

  • Extract required metadata values
  • Search for files using keyword search or Regular Expression search
  • Upload your own list of Regular Expressions

 

Review Pattern Search: scan to index files and search for Regular Expressions defined in Define RegEx

  • Drag and drop to map RegEx groups to the Target Tree
  • Map individual files from the selected RegEx group to the Target Tree
  • View RegEx results

 

Clustering: Group documents that are comparatively similar

  • Analyze clustered files and map as a unit to the target structure, or map individual files separately
  • Once a cluster is mapped, users can train the system to learn the associated document type and rename the cluster to the specified document type

 

Define Rules: map files to the target tree or apply a flag to a document

  • Use rules to action groups of files that are returned from a file property query
  • Create queries to search for, or exclude files by system generated properties such as file name, source path, age, size, etc. and custom metadata fields from a captured ECM
  • Run a rule to map files to the target tree or to flag a document
  • Automate rules to run whenever a new scan is complete

 

Action:

  • Dispose of flagged files and restructure data from the source repository based on the created Target Structure
  • Once the folders have been built out, the script will call the workspace APIs to go file-by-file and conduct the designated action
  • Schedule actions to run at your convenience


Enterprise ID

Enterprise ID projects are typically created to search repositories that are used across the enterprise for Redundant, Obsolete, and Trivial files (ROT) and Personally Identifiable Information (PII). It provides users with a large set of features to locate all data that an organization has in their possession. Regular expression and keyword searches allow you to define rules and flag for sensitive data.

Use Cases

  • Data Discovery
  • Divestments/Asset sales
  • Mergers and Acquisitions
  • Post-Merger Integration
  • Business process for GDPR
  • Business process for Privacy Compliance
  • Regulatory Compliance
  • Data Migrations
  • Data Restructuring
  • Metadata enhancement and extraction
  • Metadata mapping
  • Information Governance
  • Records Management
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Select Sources:

  • Select from multiple source repositories
  • Add new sources to scan
  • See previously added sources
  • Immediately scan sources, or schedule a scan for a later time

Select Target System: The target system is where you would like to move your files to after completing a project. This could include Shared Drives, ECMs, Microsoft Exchange Servers, and Individual Desktops.

  • Select from multiple target repositories
  • You may be choosing a new environment, or you may be moving it back into the source repository

Define Target Tree:

  • Build a folder structure that represents the organizational configuration in the destination target system
  • Create metadata groups and apply to the folder structure in the target tree

Define Pattern Search:

  • Create groups of expressions to extract and analyze values from the data
  • Extract required metadata values
  • Search for files using keyword search or Regular Expression search
  • Upload your own list of Regular Expressions

Review Pattern Search:

  • Drag and drop to map RegEx groups to the Target Tree
  • Map individual files from the selected RegEx group to the Target Tree
  • View RegEx results

Define PII: Define what your organization considers Personally Identifiable Information (PII)

  • Search for PII
  • Create groups based on PII i.e. Passports
  • Define patterns of expressions that may be contained in the company’s files
  • Create groups of expressions to extract and analyze values from the data
  • Extract required metadata values
  • Search for files using keyword search or Regular Expression search
  • Upload your own list of Regular Expressions

Review PII:

  • Search and fully index files that contain the defined PII
  • Drag and drop PII groups to the Target Tree
  • View PII results

Map Metadata: define a relationship between the Source Metadata fields aligned with the metadata fields for the Target destination

  • View and apply a list of available metadata fields that can be maintained
  • There are three types of Source Metadata
    • Basic system properties: file name, file extension, and date created/modified
    • ECM/Extended Metadata fields: scanned files coming from an ECM that have customer metadata fields already will be included in this list
    • Pattern search groups: source metadata extracted from files using Regular Expressions are included in this list

Clustering:

  • Cluster scan will group documents that are similar
  • Analyze clustered files and map as a unit to the target structure, or map individual files separately
  • Once a cluster is mapped, users can train the system to learn the associated document type and rename the cluster to the specified document type

Foldering: Map Files from the Source Tree to the Target Tree

  • Sandbox environment allows you to build out your target structure
  • Drag and drop functionality makes it easy to map files and folders
  • Easily view the source tree and the target tree on the same page

Define Rules:

  • Use rules to action groups of files that are returned from a file property query
  • Create queries to search for, or exclude files by system generated properties such as file name, source path, age, size, etc. and custom metadata fields from a captured ECM
  • Run a rule to map files to the target tree or to flag a document
  • Automate rules to run whenever a new scan is complete

Action:

  • Dispose of flagged files and restructure data from the source repository based on the created Target Structure
  • Once the folders have been built out, the script will call the workspace APIs to go file-by-file and conduct the designated action
  • Schedule actions to run at your convenience


GDPR Chapter 3

FileFacets GDPR Chapter 3 module allows users to search for, locate, identify, audit and action files containing the personal data of an individual regardless of its location within an organization’s data stores, including emails and desktops. This allows businesses to satisfy the Subject Access Request (SAR) requirements under the GDPR’s Chapter 3: Rights of the Data Subject.

Use Cases

  • Right to Access
  • Right to be Forgotten
  • Right to Data Portability
  • Right to Notification
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Define Subject
FileFacets allows users to input search criteria for data subjects and the personal data related to that subject, for example: name, address, date of birth, email and phone number. Users can do this manually or by uploading a .csv file containing the defined values, for example, a customer list or employee list.

 

Review & Action Subject Requests
FileFacets will search for and display a list of all the files that contain the personal data of a Subject based on the search terms defined. Users can audit the results and see which files may also contain the personal data of others.

Users can then audit and action the content based on the request:

Article 15 – Right of access by the data subject

  • Create a report of all files that contain the personal data of the Subject to present to the Subject

Article 17 – Right to erasure (‘right to be forgotten’)

  • Audit and exclude files that must be retained for business or other purposes
  • Delete selected files from the source repository, email or desktop
  • Provide report of deleted content

Article 20 – Right to data portability

  • Audit and exclude files that contain personal data of others or cannot shared with the Subject for business or other purposes
  • Copy files to a defined location for transferring to the Subject

 

Repository Reporting

FileFacets will search for and display a list of all the files that contain the personal data within a businesses’ data stores. Reports can be exported to use for notifying the Data Protection Authority and/or the individual(s) affected in the event of a data breach.

Users can view and audit the list based on the report and recipients:

Article 33 – Notification of a personal data breach to the supervisory authority

  • Audit Report : view and export a list of all files that contain personal data from all locations

Article 34 – Communication of a personal data breach to the data subject

  • Breach Report: view and export a list of all files that contain personal data, by specific location or repository

Get a FileFacets demo

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