iCEDQ Platform vs Data Quality Tools
When people hear about iCEDQ, the first reaction is… “Hey, I already have a data quality tool! Why do I need iCEDQ?” In this article let’s contrast iCEDQ with any other data quality tools available in the market.
What is iCEDQ?
iCEDQ is a Quality Assurance and Test Automation platform for data-centric projects and processes
such as data warehouse, CRM, data migration & conversion, ETL. It certifies the ETL processes or migration by
effective ETL Testing
and Data Migration
Testing. The product can be further used for monitoring the data processes in production. The product
emphasizes mainly process quality.
The major difference between iCEDQ & other Data Quality tools is the purpose they serve. iCEDQ
is a test automation platform for process quality whereas other Data Quality tools are a combination of data
profiling & fixing/ correction tool used in production. A breakdown of all the features is given below:
Items |
iCEDQ |
Data Quality Tools |
---|---|---|
Type of Tool | Quality Assurance Tool iCEDQ is a QA tool, purpose-built for testing data-centric projects and systems such as ETL.Other QA tools: HP Quality Center, QTP, selenium, etc. |
Data Quality Tool It is a data profiling & data correction tool.
Other tools in the class: Trillium, Informatica |
Environment/Phase in which the tool is used | Non-production environment (Dev/QA Phase) to test, validate and reconcile the data between/ across files and databases. |
Production phase to fix the data on day to day basis in conjunction with the ETL tool. |
Use cases of the tool | 1. ETL Development/Testing
2. Data Migration & System Conversion Testing. |
1. Data profiling in the early stages of the project.
2. Data fixing in a production environment. |
Features
Items |
iCEDQ |
Data Quality Tools |
---|---|---|
Requirements and Test Case Management | Yes.
The platform supports requirements and test cases management as well as linking them to physical |
No |
Data Profiling | No | Yes.
The tool discovers the patterns in data, their values, and relationships and reports any data |
ETL process Testing | Yes.
The tool support creation of rules (tests) that can validate/ test an ETL process. This is based on |
No |
Data Correction and Standardization | No | Yes.
The tool is used to run the “cleanup” task against the last data sets. It uses different rules to |
Data Match and Merge | No | Yes.
The tool allows to identify matching records and optionally link them or merge matched records based |
Data Validation Testing | Yes.
The tool allows to identify matching records and optionally link them or merge matched records based |
No |
Data Migration Testing | Yes.
The tool allows to identify matching records and optionally link them or merge matched records based |
No |
Related Articles
Agile Testing
- Practical Guide for Data Centric Testing | Blog
- Overcome Data Testing Challenges | Blog
- Agile DW Testing & Data Migration Testing | Blog
BI Testing
Data Integration
Data Management
Data Migration Testing
- Migrating Database to Redshift, Snowflake, Azure DW | Blog
- Data Migration Testing Techniques | Blog
- The Data Migration Process & Potential Risks | Blog
Data Quality
Data Warehouse
DataOps
- DataOps Implementation Guide | Blog
- AML Software Implementation & Monitoring | Blog
- Challenges Of A Data Factory | Blog