Secoda Features
What are the features of Secoda?
Data management
- Automation Features
- Data Discovery
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Secoda 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 |
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 |
Administration
Data Modelling | Tools to (re)structure data in a manner that allows extracting insights quickly and accurately | Not enough data | |
Recommendations | Analyzes data to find and recommend the highest value customer segmentations. | Not enough data | |
Workflow Management | Tools to create and adjust workflows to ensure consistency. | Not enough data | |
Dashboards and Visualizations | Presents information and analytics in a digestible, intuitive, and visually appealing way. | Not enough data |
Compliance
Sensitive Data Compliance | Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards. | Not enough data | |
Training and Guidelines | Provides guidelines or training related to sensitive data compliance requirements, | Not enough data | |
Policy Enforcement | Allows administrators to set policies for security and data governance | Not enough data | |
Compliance Monitoring | Monitors data quality and send alerts based on violations or misuse | Not enough data |
Data Quality
Data Preparation | Curates collected data for big data analytics solutions to analyze, manipulate, and model | Not enough data | |
Data Distribution | Facilitates the disseminating of collected big data throughout parallel computing clusters | Not enough data | |
Data Unification | Compile data from across all systems so that users can view relevant information easily. | Not enough data |
Functionality
Monitoring | Monitors database functionality to verify baselines are maintained or exceeded. | Not enough data | |
Alerting | Sends alerts via email, text, phone, and more when an incident or issue occcurs. | Not enough data | |
Logging | Captures logs for all database functions to garner greater information around issues or failures. | Not enough data | |
Response Time | Monitors database query time for unusual execution times | Not enough data | |
Reporting | Manually and/or automatically generates reports covering database performance | Not enough data | |
Data Visualization | Follows database monitoring live information through graphical dashboards | Not enough data | |
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 | |
Data visualisation | Creates a visual map of the data from the source to the target database for the user to see. | Not enough data | |
Data transformation | Transforms the data into the appropriate format before being transferred. | Not enough data | |
Data migration | Moves the data from one database to another. | Not enough data | |
Process various formats | The software can process numerous type of data and formats. | Not enough data | |
No-code functionality | The software can create the data map with no use of code. This is typically done via drag-and-drop. | Not enough data | |
Data manipulation | Allows the data to be merged or executed before being mapped and transformed. | Not enough data | |
Analytics | Offers built-in analytics functionality. | Not enough data | |
Reporting | Offers reporting functionality. | Not enough data | |
Structure type | Searches structured, semi-structured, and unstructured data for sensitive data. | Not enough data | |
Contextual search | Offers contextual search functions to understand factors such as file type, sensitivity, user type, location, and other metadata. | Not enough data | |
Template algorithms | Has template rules and pattern matching algorithms (PII, PCI, PHI and more) | Not enough data | |
Custom algorithms | Offers the option to create custom templates and rules based on department, user type and data type. | Not enough data | |
False-positive management | Offers false-positive management functions | Not enough data | |
Multiple file and location types | Search multiple file types (images, PDFs, etc.) and repository locations (such as on-premise databases, cloud storage, email servers, websites, etc.) | Not enough data | |
Real-time monitoring | Monitors data stores in real-time searching for newly created sensitive data. | Not enough data | |
Dashboard | Offers a dashboard showing specific location of sensitive data. | Not enough data | |
Compliance | Facilitates compliance and enables adherence to common industry regulatory standards such as GDPR, CCPA, HIPAA, PCI DSS, ISO, and others. | Not enough data | |
Reporting | Offers reporting functionality. | Not enough data | |
Automation | Reliably automates elements of the database development process. | Not enough data | |
Change validation | Validates potential database changes against development, security, and/or compliance standards. | Not enough data | |
Version control | Tracks and manages database changes, allowing users to collaborate on and change the same files without compromising the overall build by introducing conflicting code. | Not enough data | |
Real-time Analytics | Generate real-time depth analytics utilizing event metrics, logging and metadata. | Not enough data | |
Data quality monitoring | Use custom or pre-built tests for buisness rules. to ensure data quality. | Not enough data | |
Automation | Involves automation capabilities to identify and track issues, failed operations by looking at historical trends. | Not enough data | |
End to End visiblity | Complete visibility of the data pipeline, and immediately notifies the data team if any issues. Ensures cross stack visbility. | 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 | |
Business Glossary | Lets users build a glossary of business terms, vocabulary and definitions across multiple tools. | Not enough data | |
Data Discovery | Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources. | Not enough data | |
Data Profililng | Monitors and cleanses data with the help of business rules and analytical algorithms. | Not enough data | |
Reporting and Visualization | Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console. | Not enough data | |
Data Lineage | Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination. | Not enough data | |
Visibility | Provides administrators with detailed insight into changes made by database developers. | Not enough data | |
Rollbacks | Allows users to revert back to previous versions of their database builds. | Not enough data | |
Post-deployment validation | Detects and notifies teams of problematic post-deployment outcomes such as security vulnerabilities. | Not enough data | |
Anomaly identification | Identify the different type of anomalies and receive alerts. | Not enough data | |
Single pane view | The data observability environment can be viewed from a single dashboard. | Not enough data | |
Real-time alerts | Provides immediate alerts for any anomalies or expected events. | Not enough data | |
Data lineage | Establishes lineage for the data pipeline - from data warehouse to the data user. | Not enough data | |
Integrations | Support integrations with various business applications which support different data processes. Also, integrate with apps to provide alerts. | Not enough data |
Data Management
Data Integration | Consolidate data from various disparate sources in a single unified view | Not enough data | |
Data Discovery | Understand the state of data, applications, systems and services | Not enough data | |
Multi - Platform | Manage data across environments (on-premises cloud, hybrid, and multi-cloud) | Not enough data | |
Metadata | Provides metadata management and lineage capabilities | Not enough data | |
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
Data Analytics | Supports advanced analytics solutions for better business decision making | Not enough data | |
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 |
Security
Compliance | Rules and regulations inherited from source systems or defined to secure sensitive data | Not enough data | |
Governance | Grant or restrict data access and control | Not enough data | |
Data Protection | Built - In Backup and Disaster Recovery | Not enough data | |
Access Control | Authenticates and authorizes individuals to access the data they are allowed to see and use. | Not enough data | |
Roles Management | Helps identify and manage the roles of owners and stewards of data. | Not enough data | |
Compliance Management | Helps adhere to data privacy regulations and norms. | Not enough data |
Maintainence
Data Quality Management | Defines, validates, and monitors business rules to safeguard master data readiness. | Not enough data | |
Policy Management | Allows users to create and review data policies to make them consistent across the organization. | 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 |
Data management
Metadata Management | Indexes metadata descriptions for enhanced insights. | Not enough data | |
Automation Features | Based on 10 Secoda reviews. Ensures automation of metadata across the organization. Dynamically improves data management processes. | 67% (Based on 10 reviews) | |
Collaboration | Embedded collaboration using APIs and in-app integrations. | Not enough data | |
Data Lineage | Provides insights into original data sources and transformations made to data sets from source to consumption of data. | Not enough data | |
Data Discovery | Provides an interface to collect and evaluate data to identfy patterns and outliers. This feature was mentioned in 10 Secoda reviews. | 80% (Based on 10 reviews) |
Reporting
Intelligent Insights | Constantly processes metadata to provide intelligent insights. | Not enough data | |
Actionable Insights | Provides actionable insights, and generates notifications and alerts to help teams make informed decisions. | Not enough data | |
Dashboards | Supports 360 degree data visibility via a single dashboard. | 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 |
