Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Fraoula Data Auditor serves as a comprehensive tool for assessing data quality and auditing schemas, tailored for data engineering, analytics, governance, and compliance teams. It meticulously examines data structures and sample records to detect issues like schema drift, discrepancies in field types, excessive null rates, unusual values, and violations of established rules, ultimately compiling these insights into a risk report that includes recommended corrective measures. This product is beneficial for evaluating data pipelines that supply data to warehouses, analytics platforms, risk management systems, or AI applications, particularly in sectors such as finance and healthcare. Users can choose from various workflows, including a quick browser-based evaluation or more extensive audits, with options for both cloud-hosted and self-hosted deployments. The insights generated equip teams to recognize potential data risks and strategize remediation efforts before the data is utilized downstream, thus enhancing overall data integrity and reliability. By proactively addressing these issues, organizations can ensure that their data remains accurate and trustworthy for all critical applications.
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
Yes
API Access
Has API
No
Screenshots View All
No images available
Integrations
Amazon Redshift
Yes
Amazon S3
Yes
Apache Kafka
Yes
Databricks
Yes
Google Cloud BigQuery
Yes
PostgreSQL
Yes
Snowflake
Yes
dbt
Yes
Amazon Kinesis
No
Apache Airflow
Yes
Integrations
Amazon Redshift
Yes
Amazon S3
Yes
Apache Kafka
Yes
Databricks
Yes
Google Cloud BigQuery
Yes
PostgreSQL
Yes
Snowflake
Yes
dbt
Yes
Amazon Kinesis
Yes
Apache Airflow
No
Pricing Details
$0
A free tier is available. A 14-day pilot is paid; enterprise pricing is discussed with the sales team.
Free Trial
Yes
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
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
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Fraoula
Founded
2024
Country
United States
Website
www.fraoula.co
Vendor Details
Company Name
Validio
Founded
2019
Website
validio.io
Product Features
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
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
Alternatives
No Alternatives