Talentcrowd operates as a digital talent platform — providing employers with pipelines of highly vetted senior-level technology talent and on-demand engineering resources. We're tech agnostic and cost-competitive.
DataHub is an open-source data catalog and metadata management platform developed by LinkedIn. It is designed to help organizations discover, understand, and manage their data assets more effectively. DataHub enables users to catalog various types of data, including databases, tables, datasets, and data pipelines, and provides a central repository for storing metadata and lineage information.
Key Features of DataHub:
Metadata Catalog: DataHub serves as a comprehensive metadata catalog where organizations can document and index their data assets. This includes information about data sources, data schemas, data owners, and more.
Data Lineage: It tracks data lineage, showing how data flows from source to destination, including transformations and dependencies along the way. This is crucial for understanding the impact of changes and ensuring data quality.
Data Discovery: Users can search and discover datasets and data assets using a user-friendly interface. This promotes data self-service and reduces the time spent searching for relevant data.
Data Collaboration: DataHub supports collaboration by allowing users to comment on datasets, rate their quality, and share knowledge about data assets within the organization.
Data Governance: It provides data governance capabilities, enabling organizations to set access controls, ownership, and data usage policies to ensure compliance with regulations like GDPR and CCPA.
Integration: DataHub can integrate with various data tools and platforms, making it a central hub for data management. It supports integrations with data pipelines, data quality tools, and more.
Data Quality: Users can assess the quality of data assets by leveraging metadata and lineage information. Data quality metrics and profiling can be stored and analyzed within DataHub.
Use Cases for DataHub:
Data Discovery and Self-Service: Data analysts, data scientists, and other users can easily discover and access relevant data assets, reducing the time spent searching for data.
Data Governance: Organizations can use DataHub to implement data governance policies, track data lineage, and ensure compliance with data privacy regulations.
Data Lineage and Impact Analysis: Data engineers and architects can visualize data lineage to understand how data moves through pipelines and systems. This helps in impact analysis and troubleshooting.
Collaboration: Teams can collaborate by adding comments, ratings, and documentation to data assets, fostering knowledge sharing and collaboration.
Data Documentation: DataHub acts as a centralized repository for data documentation, making it easier for teams to understand data schemas and definitions.
LinkedIn originally developed DataHub to manage its vast data landscape, and it later open-sourced the platform for broader use in the data community. Many organizations have adopted DataHub to enhance their data management and governance practices, making it a valuable tool in the data ecosystem.