What does a data catalog do?

A data catalog serves as a single source of truth for an organization's data assets. Its primary functions include: Indexing and storing metadata associated with each data source. Providing a searchable interface for users to discover and access relevant data. Enhancing data governance by tracking data lineage and usage. Facilitating collaboration by allowing users to annotate, tag, and comment on data sets. Ensuring data quality and accuracy by maintaining up-to-date metadata and descriptions.

What are the different types of data catalogs?

There are primarily three types of data catalogs: Enterprise Data Catalogs: Comprehensive solutions designed for large organizations to manage vast amounts of data across different departments and systems. Domain-specific Data Catalogs: Tailored for specific industries or use cases, such as healthcare, finance, or retail, offering specialized metadata and annotations. Open-source Data Catalogs: Freely available solutions that organizations can customize and integrate into their existing data infrastructure, such as Amundsen or DataHub.

What are the Benefits of a Data Catalog?

The primary benefits of a data catalog include: Improved Data Discovery: Makes it easier for users to find relevant data sets, cutting down on time spent searching for data. Enhanced Data Governance: By providing insights into data lineage, usage, and quality, it helps maintain data integrity and compliance. Collaboration Boost: Allows teams to collaborate, share insights, and annotate data sets, fostering a data-driven culture. Data Security: Helps in understanding and tracking who accesses what data, thereby aiding in ensuring data privacy and adherence to regulations. Optimized Decision-making: With easy access to accurate and relevant data, organizations can make more informed decisions quickly.

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In today's data-driven landscape, organizations face the daunting task of not only locating and safeguarding their data but also comprehending its context and optimizing its utility. Securiti's innovative solution empowers organizations to effortlessly catalog and manage their corporate data, facilitating easy discovery, understanding, and trust-building around data assets. Say goodbye to the complexities of data governance and embrace a new era of streamlined data management with Securiti's Enterprise Data Catalog.

Securiti Enterprise Data Catalog Key Features:

Accelerate Data Analysis

Reduce time on data validation and focus on analysis to enhance business decisions.

Track Data Lineage

Follow the lifecycle of data, including its various transformations.

Collaborate Effectively

Discover, understand, and govern your corporate data efficiently.

Build Data Trust

Easily locate, interpret, and secure sensitive data.

Drive Innovation

Unleash data's full potential for revenue and growth.

Ensure Compliance

Facilitate data insights for privacy, security, & governance teams to avoid regulatory issues and fines.

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A data catalog is a centralized repository that enables organizations to manage their data assets. It offers a systematic approach to organizing, categorizing, and providing metadata around the vast amount of data generated by businesses, facilitating easier discovery and access for users. Typically, a data catalog uses metadata, descriptions, and other annotations to make data sources more understandable and discoverable.

A data catalog serves as a single source of truth for an organization's data assets. Its primary functions include:

Indexing and storing metadata associated with each data source.
Providing a searchable interface for users to discover and access relevant data.
Enhancing data governance by tracking data lineage and usage.
Facilitating collaboration by allowing users to annotate, tag, and comment on data sets.
Ensuring data quality and accuracy by maintaining up-to-date metadata and descriptions.

There are primarily three types of data catalogs:

Enterprise Data Catalogs: Comprehensive solutions designed for large organizations to manage vast amounts of data across different departments and systems.
Domain-specific Data Catalogs: Tailored for specific industries or use cases, such as healthcare, finance, or retail, offering specialized metadata and annotations.
Open-source Data Catalogs: Freely available solutions that organizations can customize and integrate into their existing data infrastructure, such as Amundsen or DataHub.

The primary benefits of a data catalog include:

Improved Data Discovery: Makes it easier for users to find relevant data sets, cutting down on time spent searching for data.
Enhanced Data Governance: By providing insights into data lineage, usage, and quality, it helps maintain data integrity and compliance.
Collaboration Boost: Allows teams to collaborate, share insights, and annotate data sets, fostering a data-driven culture.
Data Security: Helps in understanding and tracking who accesses what data, thereby aiding in ensuring data privacy and adherence to regulations.
Optimized Decision-making: With easy access to accurate and relevant data, organizations can make more informed decisions quickly.

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Data Security Posture Management
Secure sensitive data everywhere from hybrid multicloud to SaaS

View

AI Security & Governance
Establish controls for safe adoption of AI technologies including GenAI

View

Security for AI Copilots in SaaS
Unblock the biggest impediments for Safe Adoption of AI Copilots like Microsoft 365 Copilot

View

Data Access Intelligence & Governance
Monitor user access to data and enforce least privilege controls

View

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Compliance Management
Assess & improve compliance with security best practices frameworks

View

Breach Impact Analysis
Analyze breach impact & automate notifications to affected individuals

View

Data Flow Governance
Understand data lineage and secure real-time streaming data

View
Build safe enterprise AI systems

Safe Enterprise AI Copilots
Implement rule-aware AI copilots across your organization’s data anywhere

View

Data Vectorization and Ingestion
Extract info from complex Unstructured Files, convert it into AI-ready formats, and sync to vector databases

View

Data Curation and Sanitization for AI
Transform raw, unstructured files into data ready for model training and tuning

View

Context-aware LLM Firewalls
Protect AI interactions with intelligent retrieval, response, and prompt firewalls

View

Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

View
Govern data for safe innovation

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Unstructured Data Governance
Manage unstructured data to enable safe use with generative AI

View

Data Access Governance
Monitor sensitive data access and prevent unauthorized use

View

AI Governance
Establish controls for safe adoption of AI technologies including GenAI

View

Data Catalog
Enable users to easily find, understand, trust and access the data they need

View

Data Lineage
Automatically track changes and transformations of data throughout its lifecycle

View

Data Quality
Conduct data quality checks and validation across various data types

View
Automate data privacy operations

Data Mapping Automation
Manage your entire data mapping lifecycle and automate RoPA reports

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AI Governance
Comply with emerging AI regulations and ensure safe use of AI

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Data Subject Request Automation
Automate entire DSR lifecycle from consumer request intake to secure report delivery

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Automate your entire assessment lifecycle and demonstrate compliance

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Consent Management
Manage your first-party and third-party consent lifecycle from scanning to reporting

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Breach Management
Automate your incident management and optimize notifications to users & regulatory bodies

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