Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Bigeye is a platform designed for data observability that empowers teams to effectively assess, enhance, and convey the quality of data at any scale. When data quality problems lead to outages, it can erode business confidence in the data. Bigeye aids in restoring that trust, beginning with comprehensive monitoring. It identifies missing or faulty reporting data before it reaches executives in their dashboards, preventing potential misinformed decisions. Additionally, it alerts users about issues with training data prior to model retraining, helping to mitigate the anxiety that stems from the uncertainty of data accuracy. The statuses of pipeline jobs often fail to provide a complete picture, highlighting the necessity of actively monitoring the data itself to ensure its suitability for use. By keeping track of dataset-level freshness, organizations can confirm pipelines are functioning correctly, even in the event of ETL orchestrator failures. Furthermore, the platform allows you to stay informed about modifications in event names, region codes, product types, and other categorical data, while also detecting any significant fluctuations in row counts, nulls, and blank values to make sure that the data is being populated as expected. Overall, Bigeye turns data quality management into a proactive process, ensuring reliability and trustworthiness in data handling.
Description
DQOps is a data quality monitoring platform for data teams that helps detect and address quality issues before they impact your business. Track data quality KPIs on data quality dashboards and reach a 100% data quality score.
DQOps helps monitor data warehouses and data lakes on the most popular data platforms. DQOps offers a built-in list of predefined data quality checks verifying key data quality dimensions. The extensibility of the platform allows you to modify existing checks or add custom, business-specific checks as needed.
The DQOps platform easily integrates with DevOps environments and allows data quality definitions to be stored in a source repository along with the data pipeline code.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Amazon Athena
Yes
Amazon Redshift
Yes
Amazon Web Services (AWS)
Yes
Google Cloud BigQuery
Yes
MySQL
Yes
PostgreSQL
Yes
Presto
Yes
SQL Server
Yes
Slack
Yes
Snowflake
Yes
Integrations
Amazon Athena
Yes
Amazon Redshift
Yes
Amazon Web Services (AWS)
Yes
Google Cloud BigQuery
Yes
MySQL
Yes
PostgreSQL
Yes
Presto
Yes
SQL Server
Yes
Slack
Yes
Snowflake
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
$499 per month
Free Trial
No
Free Version
Yes
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
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Bigeye
Country
United States
Website
www.bigeye.com
Vendor Details
Company Name
DQOps
Founded
2021
Country
Poland
Website
dqops.com
Product Features
Product Features
Data Quality
Address Validation
Yes
Data Deduplication
No
Data Discovery
No
Data Profililng
Yes
Master Data Management
No
Match & Merge
No
Metadata Management
No