Datameer Features
Data Governance (3)
User Access Management
Allows administrators to assign role-based user access for specific data sets
Dynamic Data Masking
Hides and masks sensitive data automatically based on user permissions
Data Lineage
Provides historical insights into original data sources and transformations made to data sets
Data Preparation (4)
Search
Offers simple search capabilities to discover specific data sets
Data Quality and Cleansing
Allows users and administrators to easily clean data to maintain quality and integrity
Data Transformation
Converts data formats of source data into the format required for the reporting system without mistakes
Data Modeling
Tools to (re)structure data in a manner that allows extracting insights quickly and accurately
Collaboration (4)
Commenting
Allows users to comment on data sets to help future users better interact and interpret the data
Profiling and Classification
Permits profiling of data sets for increased organization, both by users and machine learning
Business and Data Glossary
Creates a business glossary for faster understanding by the average business user
Metadata Management
Indexes metadata descriptions for easier searching and enhanced insights
Artificial Intelligence (3)
Machine Learning Recommendations
Automates recommendations for users based on machine learning functionality
Natural Language Query
Offers natural language querying functionality for non-technical users
Automatic Data Cleansing
Cleans data to improve quality via automation
Data Source Access (3)
Breadth of Data Sources
Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others
Ease of Data Connectivity
Allows businesses to easily connect to any data source
API Connectivity
Offers API connections for cloud-based applications and data sources
Data Interaction (8)
Profiling and Classification
Permits profiling of data sets for increased organization, both by users and machine learning
Metadata Management
Indexes metadata descriptions for easier searching and enhanced insights
Data Modeling
Tools to (re)structure data in a manner that enables quick and accurate insight extraction
Data Joining
Allows self-service joining of tables
Data Blending
Provides the ability to combine data sources into one data set
Data Quality and Cleansing
Allows users and administrators to easily clean data to maintain quality and integrity
Data Sharing
Offers collaborative functionality for sharing queries and data sets
Data Governance
Ensures user access management, data lineage, and data encryption
Data Exporting (3)
Breadth of Integrations
Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools
Ease of Integrations
Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools
Data Workflows
Operationalizes data workflows to easily scale repeatable preparation needs
Functionality (5)
Identification
Correctly identify inaccurate, incomplete, or duplicated data from a data source.
Correction
Utilize deletion, modification, appending, merging, or other methods to correct bad data.
Normalization
Standardize data formatting for uniformity and easier data usage.
Preventative Cleaning
Clean data as it enters the data source to prevent mixing bad data with cleaned data.
Data Matching
Finds duplicates using the fuzzy logic technology or an advance search feature.
Management (5)
Reporting
Provide follow-up information after data cleanings through a visual dashboard or reports.
Automation
Automatically run data identification, correction, and normalization on data sources.
Quality Audits
Schedule automated audits to identify data anomalies over time based on set business rules.
Dashboard
Gives a view of the entire data quality management ecosystem.
Governance
Allows user role-based access and actions to authorization for specific tasks.
Data Management (4)
Data Integration
Integrates data and data-related technologies into a single environment.
Metadata
Provides metadata management capabilities.
Self-service
Empowers the user via a self-service capability to manage data workflows.
Automated workflows
Completely automates end-to-end data workflows across the data integration lifecycle.
Analytics (2)
Analytics capabilities
Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making.
Dasboard visualizations
Collect and displays metrics across the data integration via a dashboard.
Monitoring and Management (2)
Data Observability
Involved solely in monitoring data pipelines, sending alerts and troubleshooting data.
Testing capabilities
Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing.
Cloud Deployment (2)
Hybrid cloud support
Supports analytical platforms and data pipelines across complex hybrid environments.
Cloud migration capabilities
Supports migration of component or pipeline to different cloud environments.
Generative AI (7)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - Machine Learning Data Catalog (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Decision Making
Makes informed choices based on available data and objectives
Agentic AI - DataOps Platforms (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Decision Making
Makes informed choices based on available data and objectives



