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What is Great Expectations?

Great Expectations is designed as an open standard that promotes improved data quality through collaboration. This tool aids data teams in overcoming challenges in their pipelines by facilitating efficient data testing, thorough documentation, and detailed profiling. For the best experience, it is recommended to implement it within a virtual environment. Those who are not well-versed in pip, virtual environments, notebooks, or git will find the Supporting resources helpful for their learning. Many leading companies have adopted Great Expectations to enhance their operations. We invite you to explore some of our case studies that showcase how different organizations have successfully incorporated Great Expectations into their data frameworks. Moreover, Great Expectations Cloud offers a fully managed Software as a Service (SaaS) solution, and we are actively inviting new private alpha members to join this exciting initiative. These alpha members not only gain early access to new features but also have the chance to offer feedback that will influence the product's future direction. This collaborative effort ensures that the platform evolves in a way that truly meets the needs and expectations of its users while maintaining a strong focus on continuous improvement.

What is Aggua?

Aggua functions as an AI-enhanced data fabric platform aimed at equipping both data and business teams with easy access to their information, building trust, and providing actionable insights for more informed decision-making based on data. With just a few clicks, you can uncover essential details about your organization's data framework instead of remaining unaware of its complexities. Obtain insights into data costs, lineage, and documentation effortlessly, allowing your data engineers to maintain their productivity without interruptions. Instead of spending excessive time analyzing how changes in data types affect your pipelines, tables, and overall infrastructure, automated lineage facilitates your data architects and engineers in reducing the time spent on manual log checks, allowing them to concentrate on implementing necessary infrastructure improvements more effectively. This transition not only simplifies operations but also fosters better collaboration among teams, leading to a more agile and responsive approach to tackling data-related issues. Additionally, the platform ensures that all users, regardless of their technical background, can engage with data confidently and contribute to an organization's data strategy.

Media

Media

Integrations Supported

Amazon Redshift
Snowflake
Acryl Data
Amazon S3
Apache Airflow
Apache Spark
Astro by Astronomer
Dagster
DataHub
Databricks
Flyte
Flyte
Jupyter Notebook
Meltano
PostgreSQL
Prefect
SQL Server
Secoda
Slack
ZenML

Integrations Supported

Amazon Redshift
Snowflake
Acryl Data
Amazon S3
Apache Airflow
Apache Spark
Astro by Astronomer
Dagster
DataHub
Databricks
Flyte
Flyte
Jupyter Notebook
Meltano
PostgreSQL
Prefect
SQL Server
Secoda
Slack
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Great Expectations

Company Website

greatexpectations.io

Company Facts

Organization Name

Aggua

Date Founded

2020

Company Location

United States

Company Website

www.aggua.io

Categories and Features

Data Quality

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

Categories and Features

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

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 Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Quality

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

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