Sifflet 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
Functionality (15)
Monitoring
Monitors database functionality to verify baselines are maintained or exceeded.
Alerting
Sends alerts via email, text, phone, and more when an incident or issue occcurs.
Logging
Captures logs for all database functions to garner greater information around issues or failures.
Response Time
Monitors database query time for unusual execution times
Reporting
Manually and/or automatically generates reports covering database performance
Data Visualization
Follows database monitoring live information through graphical dashboards
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.
Real-time Analytics
As reported in 36 Sifflet reviews. Generate real-time depth analytics utilizing event metrics, logging and metadata.
Data quality monitoring
Based on 41 Sifflet reviews. Use custom or pre-built tests for buisness rules. to ensure data quality.
Automation
Involves automation capabilities to identify and track issues, failed operations by looking at historical trends. 40 reviewers of Sifflet have provided feedback on this feature.
End to End visiblity
Based on 41 Sifflet reviews. Complete visibility of the data pipeline, and immediately notifies the data team if any issues. Ensures cross stack visbility.
Management (14)
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.
Hierarchy Management
Captures and manages data hierarchy and definitions.
Reference Data Management
Helps integrate external and internal reference data such as industry codes, entity identifiers, country codes etc used to categorize information across systems.
Data Lineage
Helps understand the origination and route of data along with the transformations happening across various domains.
Metadata Management
Provides context and information for data assets stored across domains and ensures adherence to established policies and processes.
Anomaly identification
Identify the different type of anomalies and receive alerts. 40 reviewers of Sifflet have provided feedback on this feature.
Single pane view
Based on 39 Sifflet reviews. The data observability environment can be viewed from a single dashboard.
Real-time alerts
As reported in 37 Sifflet reviews. Provides immediate alerts for any anomalies or expected events.
Data lineage
Establishes lineage for the data pipeline - from data warehouse to the data user. This feature was mentioned in 39 Sifflet reviews.
Integrations
As reported in 39 Sifflet reviews. Support integrations with various business applications which support different data processes. Also, integrate with apps to provide alerts.
Functionality (4)
Multi-Domain
Centralizes the management of multiple domains of master data which includes product, customer, vendor, asset, location and pricing.
Match & Merge
Matches master data records and merges them into a single accurate record across source systems.
Relationship Mapping
Shows relationships between records and entries, defined in a repository model.
User Interface
Provides a simple customizable design environment to develop custom UIs using simple drag and drop actions.
Security (2)
Data Governance
Encompasses of policies, principles and qualities to promote access to accurate and certified master data.
Data Masking
Helps mask or hide critical information to prevent unauthorized access.
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. This feature was mentioned in 26 Sifflet reviews.
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
Agentic AI - Data Observability (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
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Agentic AI - Database Monitoring (7)
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
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives





