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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Eliminate data outages by proactively identifying and resolving data quality problems before they enter production. Achieve full test coverage of your data pipelines in just one day, going from 0 to 100%. With automatic regression testing across billions of rows, understand the impact of each code modification. Streamline change management processes, enhance data literacy, ensure compliance, and minimize the time taken to respond to incidents. Stay ahead of potential data issues by utilizing automated anomaly detection, ensuring you're always informed. Datafold’s flexible machine learning model adjusts to seasonal variations and trends in your data, allowing for the creation of dynamic thresholds. Save significant time spent analyzing data by utilizing the Data Catalog, which simplifies the process of locating relevant datasets and fields while providing easy exploration of distributions through an intuitive user interface. Enjoy features like interactive full-text search, data profiling, and a centralized repository for metadata, all designed to enhance your data management experience. By leveraging these tools, you can transform your data processes and improve overall efficiency.

Description

In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift Yes 
Google Cloud BigQuery Yes 
PagerDuty Yes 
PostgreSQL Yes 
Secoda Yes 
Slack Yes 
Snowflake Yes 
dbt Yes 
Apache Airflow Yes 
Azure Databricks Yes 
ClickHouse No 
DataHub Yes 
GitHub Yes 
Gmail No 
Looker No 
Metabase No 
Mode No 
MySQL No 
Sigma No 
Tableau No 

Integrations

Amazon Redshift Yes 
Google Cloud BigQuery Yes 
PagerDuty Yes 
PostgreSQL Yes 
Secoda Yes 
Slack Yes 
Snowflake Yes 
dbt Yes 
Apache Airflow No 
Azure Databricks No 
ClickHouse Yes 
DataHub No 
GitHub No 
Gmail Yes 
Looker Yes 
Metabase Yes 
Mode Yes 
MySQL Yes 
Sigma Yes 
Tableau Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$825 per month
Free Trial Yes 
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 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) Yes 
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) Yes 
In Person No 

Vendor Details

Company Name

Datafold

Country

United States

Website

www.datafold.com

Vendor Details

Company Name

Metaplane

Country

United States

Website

www.metaplane.dev/

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

Alternatives

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