Coginiti Features

Reports interface for standard and self-service reports is intuitive and easy to use.

Requires a minimal number of steps/clicks to answer business question.

Offers a variety of attractive graph and chart formats.

Provides business users an interface to easily design, refine and collaborate on their dashboards

Using formulas based on existing data elements, users can create and calculate new field values.

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Users can drill down and explore data to discover new insights.

Ability to search global data set to find and discover data.

Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms.

Tool automatically suggests data types, schemas and hierarchies.

Analyze current and historical trends to make predictions about future events.

Communicate complex information clearly and effectively through advanced graphical techniques.

Ability to handle large, complex, and/or siloed data sets.

Converts data formats of source data into the format required for the reporting system without mistakes.

Ability to (re)structure data in a manner that allows extracting insights fast and accurate.

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications.

Based on 17 Coginiti reviews. Allows administrators to assign role-based user access for specific data sets

Hides and masks sensitive data automatically based on user permissions 17 reviewers of Coginiti have provided feedback on this feature.

Provides historical insights into original data sources and transformations made to data sets This feature was mentioned in 18 Coginiti reviews.

Based on 20 Coginiti reviews. Offers simple search capabilities to discover specific data sets

Based on 17 Coginiti reviews. Allows users and administrators to easily clean data to maintain quality and integrity

Converts data formats of source data into the format required for the reporting system without mistakes 16 reviewers of Coginiti have provided feedback on this feature.

Tools to (re)structure data in a manner that allows extracting insights quickly and accurately This feature was mentioned in 16 Coginiti reviews.

Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications.

Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data

Based on 15 Coginiti reviews. Allows users to comment on data sets to help future users better interact and interpret the data

Permits profiling of data sets for increased organization, both by users and machine learning 17 reviewers of Coginiti have provided feedback on this feature.

Creates a business glossary for faster understanding by the average business user 16 reviewers of Coginiti have provided feedback on this feature.

Indexes metadata descriptions for easier searching and enhanced insights 17 reviewers of Coginiti have provided feedback on this feature.

As reported in 15 Coginiti reviews. Automates recommendations for users based on machine learning functionality

Offers natural language querying functionality for non-technical users This feature was mentioned in 15 Coginiti reviews.

Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others

Allows businesses to easily connect to any data source

Offers API connections for cloud-based applications and data sources

Permits profiling of data sets for increased organization, both by users and machine learning

Indexes metadata descriptions for easier searching and enhanced insights

Tools to (re)structure data in a manner that enables quick and accurate insight extraction

Allows self-service joining of tables

Provides the ability to combine data sources into one data set

Allows users and administrators to easily clean data to maintain quality and integrity

Offers collaborative functionality for sharing queries and data sets

Ensures user access management, data lineage, and data encryption

Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools

Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools

Operationalizes data workflows to easily scale repeatable preparation needs

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.

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.

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

Using formulas based on existing data elements, users can create and calculate new field values

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Allows the user to combine data from multiple sources into a functioning dataset.

Integrates data and data-related technologies into a single environment.

Provides metadata management capabilities.

Empowers the user via a self-service capability to manage data workflows.

Completely automates end-to-end data workflows across the data integration lifecycle.

Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making.

Collect and displays metrics across the data integration via a dashboard.

Involved solely in monitoring data pipelines, sending alerts and troubleshooting data.

Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing.

Supports analytical platforms and data pipelines across complex hybrid environments.

Supports migration of component or pipeline to different cloud environments.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

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.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

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

Improves performance based on feedback and experience

Makes informed choices based on available data and objectives

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

Improves performance based on feedback and experience

Makes informed choices based on available data and objectives

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

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Enables non-technical users to build dashboards through intuitive, drag-and-drop interfaces

Enables automated report generation and scheduled delivery to stakeholders

Allows dashboards and analytics to be embedded into external apps with branding flexibility

Supports integration with major data sources like cloud data warehouses, SQL/NoSQL databases, and SaaS applications

Efficiently processes large datasets with minimal lag and ensures high performance under load

Maintains performance and uptime during high traffic from multiple users or teams

Supports semantic data layers, role-based access controls, and metadata governance

Integrates with Jupyter, Python, or R for custom analytics and modeling

Provides native tools for statistical analysis, forecasting, and trend prediction

Uses AI to generate textual summaries, key takeaways, and data stories from dashboards

Allows users to query data and build reports using conversational or plain language

Detects and notifies users about KPI anomalies or significant metric changes in real time

Recommends next questions, analyses, or exploration paths using autonomous AI agents

Learns from historical user interactions to improve and personalize query results over time

Tailors dashboard views and suggestions based on user roles, access levels, and past behavior

Supports AI-driven exploration via prompts or multi-turn conversations for iterative querying