Discover, classify, organize, and report your team’s data with ease

What is data discovery and classification?

Data discovery is the process of identifying, collecting, and analyzing data from various sources to uncover patterns, relationships, and insights. It involves exploring and understanding the data landscape within an organization to make informed decisions.

Data classification is the process of organizing data into categories based on its type, sensitivity, and importance. It helps teams manage their data more effectively.

What are the features of a data discovery and classification solution?

• Automated data scanning: Automatically scans data sources to identify and catalog data

• Metadata management: Collects and organizes metadata to provide context 

• Data profiling: Analyzes data to assess quality and find patterns

• Sensitive data identification: Detects and flags sensitive information, such as PII, PHI, and financial data

• Custom classification rules: Allows users to define and apply custom classification rules based on organizational needs

• Data lineage tracking: Tracks the flow and transformation of data across systems

• Integration capabilities: Integrates with various data sources and platforms for comprehensive coverage

• Reporting and dashboards: Provides visual reports and dashboards for easy monitoring and analysis

• Access controls: Manages user permissions 

What are the benefits of a data discovery and classification solution?

A modern data catalog requires seamless integration, intuitive user interfaces, robust security features, and advanced AI-driven insights to empower teams. In return, it unlocks:

• Enhanced data governance: Improves data management practices by providing visibility and control over data assets

• Improved data quality: Ensures data accuracy and reliability by identifying and addressing data issues

• Regulatory compliance: Meet regulatory requirements by identifying and protecting sensitive data

• Efficient data management: Streamlines data organization and retrieval

• Risk mitigation: Reduces the risk of data breaches and unauthorized access 

• Better decision-making: Enable more informed and accurate business decisions through data insights

• Operational efficiency: Automates routine tasks

What’s the difference between data classification and data discovery?

• Data Discovery:

  • Focuses on identifying and exploring data from various sources.

  • Aims to understand data patterns, relationships, and insights.

  • Involves data profiling, metadata collection, and analysis.

• Data Classification:

  • Focuses on organizing data into predefined categories.

  • Aims to manage data based on its type, sensitivity, and importance.

  • Involves applying classification rules and labeling data for security and compliance purposes.

What are the different types of data classification?

1. Content-Based Classification: Organizes data based on its content, such as documents, emails, or files.

2. Context-Based Classification: Classifies data based on metadata and contextual information, such as data source or creator.

3. User-Based Classification: Relies on user input to categorize data manually.

4. Automated Classification: Uses algorithms and machine learning to classify data automatically based on patterns and predefined rules.

5. Compliance-Based Classification: Organizes data based on regulatory requirements, such as GDPR or HIPAA.

How does data.world’s data discovery and classification platform improve data teams’ abilities to organize sensitive data?

data.world’s data discovery and classification platform enhances data teams’ abilities to organize sensitive data by:

• Automated Detection: Automatically scans and identifies sensitive data across various sources, reducing manual effort and ensuring comprehensive coverage.

• Customizable Rules: Allows the creation of custom classification rules tailored to the organization's specific needs and regulatory requirements.

• Centralized Metadata Management: Consolidates metadata in a central repository, providing context and making it easier to manage and understand data.

• Real-Time Monitoring: Continuously monitors data for changes and updates classifications in real-time, ensuring data remains accurately categorized.

• Secure Access Controls: Implements robust access controls, ensuring that only authorized users can access sensitive data.

• Integration with Existing Systems: Seamlessly integrates with other data management and analytics tools, enhancing the overall data ecosystem.

• User-Friendly Dashboards: Provides intuitive dashboards and reports, enabling data teams to quickly assess data classifications and take appropriate actions.

• Enhanced Compliance: Helps maintain compliance with data protection regulations by accurately identifying and securing sensitive information.