iceDQ Features
Trusted by industry, secure & scalable
iceDQ is the only integrated platform for data testing, monitoring, and observability, offering vast capabilities to meet the most complex data reliability requirements.
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| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| Rules and AI: Automatically generate rules and metrics. | |||
| Low code-No code: Leverage a library of pre-built out-of-box templates and checks to set up your test cases quickly and efficiently. | |||
| Exception Report: Get granular data exceptions at record and column level. | |||
| Reporting Dashboard: Visualize pre-built DQ dashboards. | |||
| DevOps Integration: Automate data quality checks within your CI/CD pipeline for continuous monitoring. | |||
| Test Case Management Integration: Connect with TCM tools to automate data validation. | |||
| Multi-Source Data Comparison: Compare and validate data sets from different sources. | |||
| Performance and Scalability: Scales efficiently to accommodate growing data volumes without compromising performance. | |||
| Multi-Tenancy: Efficiently manage and isolate data for multiple tenants within a single deployment, ensuring security and resource optimization. | |||
| API First: Design and build your integrations with a robust API-first approach, ensuring seamless connectivity across systems. | |||
| 150+ Connectors: Connect to any databases, files, applications, systems, data lakes, big data platforms, and more. | |||
| Anomaly Detection: Utilize both machine learning and rule-based methods for comprehensive anomaly detection. | – | – |
| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| Supported Data Source Authentications: User Authentication, Windows Authentication, Active Directory, Kerberos Keytab, Kerberos Ticket Cache, OAuth 2.0, AWS IAM, Azure Key Vault, and more. | |||
| Single Sign-On: Simplify logins and access with Single Sign-On (SSO) integration. | |||
| Integrated Key Vault: Ensures secure access and management of encryption keys for heightened data protection. | |||
| LDAP / Active Directory: Integrate seamlessly with LDAP and Active Directory for centralized user management and authentication. | |||
| End-to-End Encryption: Data is fully encrypted in transit and at rest, ensuring complete security and privacy. |
| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| Checksum Rule: Checksum rule is used to compare row count, sum, average, min/max, and other aggregated values. | – | ||
| Reconciliation Rule: Recon rule compares data between the source and target. Database vs database, database vs files, API vs database, BI reports vs database, and more. | – | ||
| Validation Rule: Validation rule allows users to test the formats, lengths, ranges, business logic, and other aspects of data in a specific dataset. | – | ||
| Pushdown Rule: Use this rule to offload data validation processing to the source database or system. This rule is typically used for duplicate checks and type II dimension tests. | – | ||
| Script Rule: Write custom groovy script to execute any pre-processing or post-processing tasks and achieve end-to-end testing. | – | ||
| Regression Suite: Use our workflows feature to run a collection of rules in a sequence for Regression Testing or Release Testing. | – | ||
| Macro Metrics: Focus on aggregated data such as freshness and volume metrics. | – | – | |
| Micro Metrics: Focus on individual records in the data such as completeness and accuracy. | – | – | |
| Segmented Metrics: Segmented metrics are simply macro metrics applied to specific data subgroups, like volume by country code. | – | – | |
| Autometrics: The system offers built-in data profiling and automatic metric generation. This enables rapid scaling of observability. | – | – |
| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| Databases: Support for all kinds of databases such as DB2, MySQL, Oracle, PostgreSQL and more. | |||
| Data Lakes: Support for Amazon S3, Azure Blob Storage, Azure Data Lake Storage, Google Cloud BigLake and more. | |||
| Files: Connect, test, and write queries on various file types such as Excel, flat files, JSON, XML, Parquet, and more. | |||
| Cloud: Seamlessly integrate with popular cloud data platforms like Snowflake, Redshift, BigQuery, and others. | |||
| Big Data: iceDQ scales to conquer big data challenges, seamlessly integrating with Hadoop, Spark, and other big data frameworks. |
| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| ALM: Seamlessly integrate with ALM tools like HP ALM and X-Ray for defect tracking and resolution. | |||
| Ticketing System: Easily integrate with ticketing systems like Jira and ServiceNow. | |||
| Scheduler: Out-of-Box integrations available for schedulers like Airflow, Autosys, and Control-M. |
| Functionalities | Data Testing | Data Monitoring | Data Observability |
|---|---|---|---|
| Parameterization: Leverage parameters to define reusable rules that adapt to different environments and data sets. | – | ||
| User-Defined Functions: Extend iceDQ's capabilities by creating custom UDFs (User-Defined Functions) within the platform. | – | ||
| Rules Wizard: The Rules Wizard helps you create bulk rules in a flash. | – | ||
| Built-in Scheduler: Trigger rules and workflows based on a time-based schedule. | |||
| Alerts & Notifications: Receive timely alerts and notifications about data issues via email, Teams, or Slack. | |||
| User Role-based Controls: Assign roles with granular permissions to specific users. | |||
| Group-based Controls: Streamline user access control by creating groups and assigning roles at the group level. | |||
| External-Library Support: Users can import Java or custom libraries for use in advanced scripting rules. | |||
| Custom Tags & Label Support: Add custom labels and tags to rules, workflows, and checks for improved reporting, and easier identification of rule types. | |||
| Central Repository: Simplified management with a central repository for rules, setting and other critical configurations. | |||
| Audit History: Track every action with a detailed audit history. | |||
| Import-Export: Import or export rules, workflows and other configuration between environments. | |||
| Architecture: Based on microservices and follows an API-first approach. | |||
| Deployment: SaaS, On-premises, Cloud, more… | |||
| Query Builder: The intuitive query builder eliminates the need to write complex queries. | – |
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