Data Intelligence Platform BigID

BigID’s data intelligence platform enables organizations to know their enterprise data and take action for privacy, protection, and perspective.

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Customers deploy BigID to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape, weather they are structured- or non-structured based.

Data Inventory & Data Catalog

This discipline is intended to ensure that the sensitive data can be identified and classified within the organization. An inventory defines the basis for further measures, but also for assessing the current risk exposure of processing sensitive data. The inventory covers structured (e.g. applications with databases) as well as unstructured (e.g. file storage such as SharePoint) data storage sources.

This supports requests for information, corrections and deletion from individuals, as the inventory knows which data is stored and processed in which systems. In addition, possible deviations from the norm in all data sources and data owners should be recognized and monitored using policies. In this way, the corrective measures can be initialized and checked by means of cleanup jobs. On this basis, the ability to audit internal and external audit bodies is also ensured.

BigID – Data Intelligence Platform as Discovery Foundation

BigID's software is redefining how organizations find, analyze, and mitigate personal identifiying data and mitigate the risks to today's personal information (PI), privacy and data governance issues. BigID discovers and inventories PI in structured, unstructured and large data stores. It monitors how the PI is accessed to automate mapping of data flows, analyzes risk factors like open access and duplicates to improve data security, and provides collaboration and reporting capabilities necessary for data protection compliance and data governance regulations are required.

BigID adds another dimension to understanding data. Classic methods of pattern matching and metadata lack detail and context. BigID adds modern technologies like advanced machine learning while reading and analyzing actual data. Supported by neural network based enhanced classification, your data centric strategy builds on a holistic view of the data landscape. Features like tagging and labeling allow to find a common naming across all data sources, improving clarity in communication between tech and business data workers.

Data Sources

A data source is a data repository that BigID scans to give detailed information about the (sensitive) data stored in it. BigID can connect to almost any type of data source, including structured and unstructured formats.

Get the list of available connectors here: https://bigid.com/data-coverage/

Automate Action With Apps for Data Privacy, Protection, and Perspective

BigID helps organizations manage and protect their data on-prem and in the cloud, enables organizations to meet data privacy and protection regulations, and provides unmatched coverage for all types of data across all data stores. BigID redefines data privacy and protection with privacy-centric security:

Discover and map all types of data across the enterprise IT infrastructure
Automatically classify, correlate, and catalog identity & entity data into profiles
Automate data labeling and tagging based on advanced data insights
Calibrate risk per attribute, data source, and residency
Manage and protect enterprise data with advanced data intelligence
Automate data privacy and protection to operationalize compliance

BigID provides an open platform to create customized data sources using the SDK if the connector is not available from the standard. Additional BigID only ready the data source agentless and does not copy any data during scanning. One additional advantage is that connectors are available as API to reach maximum coverage for your inventory.

BigID App Framework

Besides the Discovery Foundation Features, BigID offers additional set of functions that can be added such as:

Privacy Apps

Move beyond policy and process to data-centric privacy compliance and automation.

DSAR Automation

Automate data access rights fulfilment and reporting at scale.

Deletion Validation

Ensure ongoing, automated validation of individual deletion requests.

Third Party Data Sharing

Manage, monitor & validate third party data transfer.

Data Flow Mapping

Find & classify PL and PLL to automate inventory & data mapping.

PL Classification

ML-driven classification for direct and indirect identifiers based on association

Consent Governance

Correlate, Govern, and Orchestrate Consent and Preferences.

Data Retention

Assign and enforce retention timeless to attributes based on policy.

Policy Enforcement

Define business-specific policies to manage, detect & alert on data transfers & misuse.

Data Inventory

Maintain automated, up-to-date inventory of data by person, residency, data source, data type.

Protection Apps

Streamline data and AI governance with deeper data intelligence.

380 Visibility

Get broad coverage in context with other types of data across data centres and in the cloud - and seamlessly integrate data intelligence insights in a single pane of glass.

Dark Data Discovery

Leverage machine learning and deep learning for Named Entity Recognition (NER) to uncover dark data, discover relationships between data, and protect and organization's jewels.

ML Classification

Automatically classify sensitive data beyond Regular Expressions (RegEx) - classify by regulation, document type, policy, attributes, person, and more.

Data Access Insights

Identify overexposed data and get insights on access intelligence to reduce risk and protect personal & sensitive data across your enterprise data stores.

Automatic Labelling

Automatically label and tag files based on existing classifications - and align labels with automated workflows for advanced data protection and lifecycle management.

Policy Enforcement

Automate policy checks and enforcement and compliance, and integrate with DRM, DLP, encryption, tagging, and other point tools.

Data Remediation

Remediate at-risk data and proactively protect sensitive data with deep data intelligence - and take action for security, privacy, and governance remediation.

Breach Notification

Accurately determine impacted users following & breach incident, meet breach notification requirements, and speed up investigation responses.

Risk Scoring

Prioritize risk remediation with risk scoring, and build custom risk metrics based on data type, location, access, consent, and more.

Perspective Apps

Streamline data and AI governance with deeper data intelligence.

Data Catalogue

Catalogue in context: See attributes, metadata, and context around your data to make intelligence decision.

Unified Inventory

Automatically Inventory enterprise data via machine learning across siloed data assets with broad data coverage.

Metadata Exchange

Leverage a bi-directional metadata exchange: import business glossaries, discover the full scope of data, map, business terms.

Data Quality

Actively monitor the consistency, accuracy, completeness and validity of your data.

Metadata Management

Enrich technical metadata with business and operational metadata for full visibility.

Data Labelling

Automatically label data (e.g. residency, risk classification) and propagate labels automatically across data sources.

Discovery & Classification

Security professionals need to be able to discover and identify any personal information that their company is responsible for, including:

PII – personally identifiable information
PI – personal information (or how data is related to an individual)
IP & confidential business data Other sensitive data that’s particularly vulnerable to attack

Classification and discovery that relies exclusively on regular expressions, keywords, and pattern-matching is dependent on data that follows a specific format, and is unable to identify and categorize the broader scope of personal information. A privacy-centric approach to security requires that organizations are able to identify, map, and categorize all sensitive data - regardless of what type or format it is.

Risk Management

You can’t protect what you can’t see, which is why it’s more important than ever to proactively pursue full visibility of an organization’s sensitive data – wherever it’s stored. In order to measure data risk effectively, organizations need to be able to:

Maintain an accurate and up to date inventory of sensitive data
Identify vulnerable & high-risk data based on access, content, and attributes
Monitor and validate consent & business policy
Automate data protection based on advanced insight

Context-Driven Data Protection Policies

Data protection policies can help protect data throughout the information lifecycle, adding contextual and operational elements to the mix in order to better secure and define high-risk data that organizations need to collect. In the same way that organizations look to reduce and manage the attack surface, focusing on what data to secure and understanding why it is sensitive is critical to effective data protection.

Security professionals can add labeling, lifecycle management, data minimization, and risk calibration to their arsenal in order to help minimize risk and protect sensitive data. Reviewing permissions and monitoring for high-risk data policies like open access helps reduce risk, enables organizations to create playbooks for security remediation triggered by policy violations, and accelerates compliance with data privacy and protection regulations across the board.

Privacy Engineering

Privacy-by-design (PbD) provides a set of principles to help guide privacy and data protection standards, and privacy engineers are the ones who implement those standards into an organization’s business processes.

These privacy and data protection standards help implement data privacy and protection policies including: