Soda Features
Functionality (8)
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Identification
Correctly identify inaccurate, incomplete, or duplicated data from a data source.
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Normalization
Standardize data formatting for uniformity and easier data usage.
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Data Matching
Finds duplicates using the fuzzy logic technology or an advance search feature.
Real-Time Data
Receive data and information in real time
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Real-time Analytics
Generate real-time depth analytics utilizing event metrics, logging and metadata.
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Data quality monitoring
Use custom or pre-built tests for buisness rules. to ensure data quality.
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Automation
Involves automation capabilities to identify and track issues, failed operations by looking at historical trends.
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End to End visiblity
Complete visibility of the data pipeline, and immediately notifies the data team if any issues. Ensures cross stack visbility.
Management (9)
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Reporting
Provide follow-up information after data cleanings through a visual dashboard or reports.
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Quality Audits
Schedule automated audits to identify data anomalies over time based on set business rules.
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Dashboard
Gives a view of the entire data quality management ecosystem.
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Governance
Allows user role-based access and actions to authorization for specific tasks.
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Anomaly identification
Identify the different type of anomalies and receive alerts.
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Single pane view
The data observability environment can be viewed from a single dashboard.
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Real-time alerts
Provides immediate alerts for any anomalies or expected events.
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Data lineage
Establishes lineage for the data pipeline - from data warehouse to the data user.
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Integrations
Support integrations with various business applications which support different data processes. Also, integrate with apps to provide alerts.
Generative AI (4)
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AI Text Generation
Allows users to generate text based on a text prompt.
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AI Text Generation
Allows users to generate text based on a text prompt.
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AI Text Summarization
Condenses long documents or text into a brief summary.
Generative AI
Use AI to generate content in the form of text, images, videos, etc.
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
Additional Functionality (35)
Metadata Management
Indexes metadata descriptions for easier searching and enhanced insights
Collaboration Tools
Provides a channel for team members to share media files, communicate, and work together
Search/Filter
Search and filter data across systems to locate required information by entering keywords or certain criteria
Workflow Management
Create, design and manage workflows for repetitive tasks
AI Copilot
A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users
Third-Party Integrations
Set up connections to third-party platforms to improve business processes
Data Synchronization
Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency
Data Import/Export
Import and export data to and from software applications
Customizable Rules
Rules followed by the software/AI can be configured by users to suit their specific needs
Master Data Management
Verify, organize, manage & store enterprise data assets in a centralized repository
Monitoring
Observe and track the demand, usage, progress or quality of a system, product, or user
Data Transformation
Translate EDI formats into data suitable for use with company applications.
Multiple Data Sources
Allows users to manage data from a number of sources
Self Service Portal
Online portal through which end users can access the system, manage tasks, or obtain information
Customer Database
A collection of customer information such as contact details, demographics, previous interactions, etc.
Data Verification
Process of checking different types of data for accuracy to avoid errors or inconsistencies
Data Migration
Move from one database to another, or upgrade the version of database software being used
Multi-Language
Manage and support multiple languages
Single Sign On
Allow users to access multiple services after entering their login credentials once
Duplicate Detection
Compare new data with existing records to detect duplicate entries
Email Address Extraction
Extract email addresses from multiple data sources
Reporting/Analytics
View and track pertinent metrics to find patterns and gain insights from data
Data Profiling
Examines, analyzes, and organizes data to create relevant summaries or graphs.
Data Extraction
Automatically retrieve and pull information from documents, websites, images, data sets, and other sources
Data Mapping
Track the management and flow of data throughout the organization
Address Validation
Verifies and confirms the accuracy of an address
Match & Merge
Looking at data from different sources and finding possible duplicates, or identical matches
Performance Metrics
A set of indicators that tracks the performance of networks, applications, systems, teams, etc.
Visual Analytics
Interact with data visualization elements, such as charts and graphs, to drill down into data
Version Control
Track revisions and updates made to files and navigate between different versions
API
Application programming interface that allows for integration with other systems/databases
Data Capture and Transfer
Import, collect, and capture data from multiple sources
Access Controls/Permissions
Define levels of authorization for access to specific files or systems
Compliance Management
Track and manage adherence to policies for any service, product, process, or supplier
Data Discovery
Discover and connect variety of data sources to the application for analysis
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