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Description

Great Expectations serves as a collaborative and open standard aimed at enhancing data quality. This tool assists data teams in reducing pipeline challenges through effective data testing, comprehensive documentation, and insightful profiling. It is advisable to set it up within a virtual environment for optimal performance. For those unfamiliar with pip, virtual environments, notebooks, or git, exploring the Supporting resources could be beneficial. Numerous outstanding companies are currently leveraging Great Expectations in their operations. We encourage you to review some of our case studies that highlight how various organizations have integrated Great Expectations into their data infrastructure. Additionally, Great Expectations Cloud represents a fully managed Software as a Service (SaaS) solution, and we are currently welcoming new private alpha members for this innovative offering. These alpha members will have the exclusive opportunity to access new features ahead of others and provide valuable feedback that will shape the future development of the product. This engagement will ensure that the platform continues to evolve in alignment with user needs and expectations.

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
Apache Airflow
Apache Spark
MySQL
PostgreSQL
Prefect
SQL Server
Slack
Snowflake
Acryl Data
Amazon QuickSight
Census
Datadog
Firebolt
Google Cloud Platform
Looker
Meltano
Microsoft Azure
Microsoft Teams

Integrations

Amazon Redshift
Amazon S3
Apache Airflow
Apache Spark
MySQL
PostgreSQL
Prefect
SQL Server
Slack
Snowflake
Acryl Data
Amazon QuickSight
Census
Datadog
Firebolt
Google Cloud Platform
Looker
Meltano
Microsoft Azure
Microsoft Teams

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

Great Expectations

Website

greatexpectations.io

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

Alternatives

Alternatives

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