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Average Ratings 2 Ratings

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ease
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design
support

Description

Assisting businesses in actively overseeing their comprehensive data quality lifecycle is achieved through the implementation of contextual data quality assessments, anomaly detection, and corrective measures. By revealing anomalies and relevant metadata, teams are empowered to implement necessary corrective actions effectively. Automated remediation workflows can be initiated to swiftly and efficiently address any errors that arise. This proactive approach helps ensure superior data quality, safeguarding against inaccuracies that could undermine business decision-making. Additionally, the SLA chart offers a detailed overview of service level agreements, showcasing the total number of monitoring activities conducted and any violations encountered. Such insights can significantly aid in pinpointing specific areas of your data that may necessitate further scrutiny or enhancement. Ultimately, maintaining robust data quality is essential for driving informed business strategies and fostering growth.

Description

Effortlessly monitor thousands of tables through machine learning-driven anomaly detection alongside a suite of over 50 tailored metrics. Ensure comprehensive oversight of both data and metadata while meticulously mapping all asset dependencies from ingestion to business intelligence. This solution enhances productivity and fosters collaboration between data engineers and consumers. Sifflet integrates smoothly with your existing data sources and tools, functioning on platforms like AWS, Google Cloud Platform, and Microsoft Azure. Maintain vigilance over your data's health and promptly notify your team when quality standards are not satisfied. With just a few clicks, you can establish essential coverage for all your tables. Additionally, you can customize the frequency of checks, their importance, and specific notifications simultaneously. Utilize machine learning-driven protocols to identify any data anomalies with no initial setup required. Every rule is supported by a unique model that adapts based on historical data and user input. You can also enhance automated processes by utilizing a library of over 50 templates applicable to any asset, thereby streamlining your monitoring efforts even further. This approach not only simplifies data management but also empowers teams to respond proactively to potential issues.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift
Amazon S3
Google Cloud BigQuery
Snowflake
Amazon EMR
Amazon QuickSight
Apache Airflow
Azure Blob Storage
Census
Databricks
Datadog
Fivetran
Google Cloud Platform
Microsoft Azure
Microsoft Teams
SQL Server
Slack
Stitch
Tableau
dbt

Integrations

Amazon Redshift
Amazon S3
Google Cloud BigQuery
Snowflake
Amazon EMR
Amazon QuickSight
Apache Airflow
Azure Blob Storage
Census
Databricks
Datadog
Fivetran
Google Cloud Platform
Microsoft Azure
Microsoft Teams
SQL Server
Slack
Stitch
Tableau
dbt

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Qualytics

Founded

2020

Country

United States

Website

qualytics.co

Vendor Details

Company Name

Sifflet

Country

United States

Website

www.siffletdata.com

Product Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Product Features

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

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