Datameer Features
What are the features of Datameer?
Data Source Access
- Ease of Data Connectivity
Data Interaction
- Metadata Management
- Data Modeling
- Data Joining
- Data Blending
- Data Sharing
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Datameer Categories on G2
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Data Governance
User Access Management | Allows administrators to assign role-based user access for specific data sets | Not enough data | |
Dynamic Data Masking | Hides and masks sensitive data automatically based on user permissions | Not enough data | |
Data Lineage | Provides historical insights into original data sources and transformations made to data sets | Not enough data |
Data Preparation
Search | Offers simple search capabilities to discover specific data sets | Not enough data | |
Data Quality and Cleansing | Allows users and administrators to easily clean data to maintain quality and integrity | Not enough data | |
Data Transformation | Converts data formats of source data into the format required for the reporting system without mistakes | Not enough data | |
Data Modeling | Tools to (re)structure data in a manner that allows extracting insights quickly and accurately | Not enough data |
Collaboration
Commenting | Allows users to comment on data sets to help future users better interact and interpret the data | Not enough data | |
Profiling and Classification | Permits profiling of data sets for increased organization, both by users and machine learning | Not enough data | |
Business and Data Glossary | Creates a business glossary for faster understanding by the average business user | Not enough data | |
Metadata Management | Indexes metadata descriptions for easier searching and enhanced insights | Not enough data |
Artificial Intelligence
Machine Learning Recommendations | Automates recommendations for users based on machine learning functionality | Not enough data | |
Natural Language Query | Offers natural language querying functionality for non-technical users | Not enough data | |
Automatic Data Cleansing | Cleans data to improve quality via automation | Not enough data |
Data Source Access
Breadth of Data Sources | Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others | Not enough data | |
Ease of Data Connectivity | As reported in 10 Datameer reviews. Allows businesses to easily connect to any data source | 92% (Based on 10 reviews) | |
API Connectivity | Offers API connections for cloud-based applications and data sources | Not enough data |
Data Interaction
Profiling and Classification | Permits profiling of data sets for increased organization, both by users and machine learning | Not enough data | |
Metadata Management | Based on 10 Datameer reviews. Indexes metadata descriptions for easier searching and enhanced insights | 80% (Based on 10 reviews) | |
Data Modeling | As reported in 10 Datameer reviews. Tools to (re)structure data in a manner that enables quick and accurate insight extraction | 87% (Based on 10 reviews) | |
Data Joining | As reported in 10 Datameer reviews. Allows self-service joining of tables | 90% (Based on 10 reviews) | |
Data Blending | Provides the ability to combine data sources into one data set 10 reviewers of Datameer have provided feedback on this feature. | 88% (Based on 10 reviews) | |
Data Quality and Cleansing | Allows users and administrators to easily clean data to maintain quality and integrity | Not enough data | |
Data Sharing | As reported in 10 Datameer reviews. Offers collaborative functionality for sharing queries and data sets | 87% (Based on 10 reviews) | |
Data Governance | Ensures user access management, data lineage, and data encryption | Not enough data |
Data Exporting
Breadth of Integrations | Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools | Not enough data | |
Ease of Integrations | Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools | Not enough data | |
Data Workflows | Operationalizes data workflows to easily scale repeatable preparation needs | Not enough data |
Functionality
Identification | Correctly identify inaccurate, incomplete, or duplicated data from a data source. | Not enough data | |
Correction | Utilize deletion, modification, appending, merging, or other methods to correct bad data. | Not enough data | |
Normalization | Standardize data formatting for uniformity and easier data usage. | Not enough data | |
Preventative Cleaning | Clean data as it enters the data source to prevent mixing bad data with cleaned data. | Not enough data | |
Data Matching | Finds duplicates using the fuzzy logic technology or an advance search feature. | Not enough data |
Management
Reporting | Provide follow-up information after data cleanings through a visual dashboard or reports. | Not enough data | |
Automation | Automatically run data identification, correction, and normalization on data sources. | Not enough data | |
Quality Audits | Schedule automated audits to identify data anomalies over time based on set business rules. | Not enough data | |
Dashboard | Gives a view of the entire data quality management ecosystem. | Not enough data | |
Governance | Allows user role-based access and actions to authorization for specific tasks. | Not enough data |
Data Management
Data Integration | Integrates data and data-related technologies into a single environment. | Not enough data | |
Metadata | Provides metadata management capabilities. | Not enough data | |
Self-service | Empowers the user via a self-service capability to manage data workflows. | Not enough data | |
Automated workflows | Completely automates end-to-end data workflows across the data integration lifecycle. | Not enough data |
Analytics
Analytics capabilities | Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making. | Not enough data | |
Dasboard visualizations | Collect and displays metrics across the data integration via a dashboard. | Not enough data |
Monitoring and Management
Data Observability | Involved solely in monitoring data pipelines, sending alerts and troubleshooting data. | Not enough data | |
Testing capabilities | Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing. | Not enough data |
Cloud Deployment
Hybrid cloud support | Supports analytical platforms and data pipelines across complex hybrid environments. | Not enough data | |
Cloud migration capabilities | Supports migration of component or pipeline to different cloud environments. | Not enough data |
Generative AI
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data |
