Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Automatically extract and visualize data lineage by mapping the flow of data from its origin to its destination. This comprehensive data lineage management solution gathers and assesses the lineage of critical data, illustrating the data flow and derivation rules from the source to the target. Understanding data lineage involves tracing the journey of data as it is processed, transformed, and utilized, thereby revealing the flow and derivation rules that govern it. The solution offers a multi-tier, column-level data lineage graph alongside a detailed list that tracks data progression from source to target. Users can drill down into data lineage at the business system, table, and column levels for a granular view. Additionally, it provides parsers for various environments to facilitate thorough analysis, including support for Big Data technologies. Utilizing our patented technology, the system conducts path-sensitive dynamic string analysis and data flow analysis within programs, enhancing the understanding of data movement. This capability ensures that organizations maintain a clear view of their data's journey, thereby fostering better data governance and compliance.
Description
Examine the usage of your data assets, focusing on aspects like popularity, utilization, and schema coverage. Gain vital insights into your data assets, including their quality and usage metrics. You can easily locate and filter the necessary data by leveraging metadata tags and descriptions. Additionally, these insights will help you drive data governance and establish clear ownership within your organization. By implementing a streamlined lineage from data lakes to warehouses, you can enhance collaboration and accountability. An automatically generated field-level lineage map provides a comprehensive view of your entire data ecosystem. Moreover, anomaly detection systems adapt by learning from your data trends and seasonal variations, ensuring automatic backfilling with historical data. Thresholds driven by machine learning are specifically tailored for each data segment, relying on actual data rather than just metadata to ensure accuracy and relevance. This holistic approach empowers organizations to better manage their data landscape effectively.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon Kinesis
No
Amazon Redshift
No
Amazon S3
No
Apache Kafka
No
Azure Data Lake
No
Azure Synapse Analytics
No
Databricks
No
Gmail
No
Google Cloud BigQuery
No
Google Cloud Pub/Sub
No
Integrations
Amazon Kinesis
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Apache Kafka
Yes
Azure Data Lake
Yes
Azure Synapse Analytics
Yes
Databricks
Yes
Gmail
Yes
Google Cloud BigQuery
Yes
Google Cloud Pub/Sub
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
We-Bridge
Founded
2020
Country
United States
Website
we-bridge.com/products/datahawk/
Vendor Details
Company Name
Validio
Founded
2019
Website
validio.io
Product Features
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
Product Features
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No