Great Expectations Features

Correctly identify inaccurate, incomplete, or duplicated data from a data source.

Utilize deletion, modification, appending, merging, or other methods to correct bad data.

Standardize data formatting for uniformity and easier data usage.

Clean data as it enters the data source to prevent mixing bad data with cleaned data.

Finds duplicates using the fuzzy logic technology or an advance search feature.

Receive data and information in real time

Generate real-time depth analytics utilizing event metrics, logging and metadata.

Use custom or pre-built tests for buisness rules. to ensure data quality.

Involves automation capabilities to identify and track issues, failed operations by looking at historical trends.

Complete visibility of the data pipeline, and immediately notifies the data team if any issues. Ensures cross stack visbility.

Provide follow-up information after data cleanings through a visual dashboard or reports.

Automatically run data identification, correction, and normalization on data sources.

Schedule automated audits to identify data anomalies over time based on set business rules.

Gives a view of the entire data quality management ecosystem.

Allows user role-based access and actions to authorization for specific tasks.

Identify the different type of anomalies and receive alerts.

The data observability environment can be viewed from a single dashboard.

Provides immediate alerts for any anomalies or expected events.

Establishes lineage for the data pipeline - from data warehouse to the data user.

Support integrations with various business applications which support different data processes. Also, integrate with apps to provide alerts.

Allows users to generate text based on a text prompt.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Use AI to generate content in the form of text, images, videos, etc.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Indexes metadata descriptions for easier searching and enhanced insights

Provides a channel for team members to share media files, communicate, and work together

Search and filter data across systems to locate required information by entering keywords or certain criteria

Create, design and manage workflows for repetitive tasks

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Set up connections to third-party platforms to improve business processes

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Import and export data to and from software applications

Rules followed by the software/AI can be configured by users to suit their specific needs

Verify, organize, manage & store enterprise data assets in a centralized repository

Observe and track the demand, usage, progress or quality of a system, product, or user

Translate EDI formats into data suitable for use with company applications.

Allows users to manage data from a number of sources

Online portal through which end users can access the system, manage tasks, or obtain information

A collection of customer information such as contact details, demographics, previous interactions, etc.

Process of checking different types of data for accuracy to avoid errors or inconsistencies

Move from one database to another, or upgrade the version of database software being used

Manage and support multiple languages

Allow users to access multiple services after entering their login credentials once

Compare new data with existing records to detect duplicate entries

Extract email addresses from multiple data sources

View and track pertinent metrics to find patterns and gain insights from data

Examines, analyzes, and organizes data to create relevant summaries or graphs.

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Track the management and flow of data throughout the organization

Verifies and confirms the accuracy of an address

Looking at data from different sources and finding possible duplicates, or identical matches

A set of indicators that tracks the performance of networks, applications, systems, teams, etc.

Interact with data visualization elements, such as charts and graphs, to drill down into data

Track revisions and updates made to files and navigate between different versions

Application programming interface that allows for integration with other systems/databases

Import, collect, and capture data from multiple sources

Define levels of authorization for access to specific files or systems

Track and manage adherence to policies for any service, product, process, or supplier

Discover and connect variety of data sources to the application for analysis