6 Dimensions of Data Quality | Blog
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All About ETL Testing, Data Migration & Data Warehouse Testing
AML Software Implementation & Monitoring | Blog
AML software is a downstream system that consumes data from multiple sources. AML software analyzes data based on compliance models. This results in suspicious activity reports. Further, they also monitor data for regulations such as FATCA, trade restrictions, sanctions, and watch list.
However, if the incoming data is not good then these results cannot be relied upon. It is basically at the mercy of upstream systems.
iCEDQ is an in-memory data audit rules engine. It sits between the data sources and downstream systems such as ALM. It can validate and reconciliation data coming from multiple data sources. Thus, managing data issues before it affect the downstream system.
Audit Missing Element in Data Management & Data Governance | Blog
Perhaps the most astonishing fact, however, is that IT has been blind for so long to the need for monitoring and metering (Auditing) for data health, and yet this fundamental engineering concept. For instance, Figure 1 illustrates a centrifugal steam engine governor.
Data Migration Testing Techniques | Blog
We discussed the potential risks involved with the data migration process in our last iCEDQ insight. As previously mentioned, data migration is an important process where data from one system is transferred to a new, target system. The threat of data loss, data corruption, extended downtime, and application crashes make the data migration process risky. Amid these potential risks, a proper quality assurance process must be implemented to test the possibility of various risks of affecting the data migration process.
DataOps Implementation Guide | Blog
The team is usually divided into development, QA, operations and business users. In almost all Data Integration projects, development teams try to build and test ETL processes, reports as fast as possible and throw the code across the wall to the operations teams and business users. However, when the data issues start appearing in production, business users become unhappy. They point fingers at Operations people, who in turn point fingers at QA people. The QA group then puts the blame on the development teams.
ETL Testing & Data Quality Governance Software | Blog
Data has become critical to the business. Hence, enterprises are investing time, money and resources in data-centric systems such as data warehouse, MDM, CRM & migration projects. However, all research done by independent agencies indicates that, There is such a high failure/delays in implementations of data-centric projects, Users still don’t trust data coming from data warehouses.
Agile DW Testing & Data Migration Testing | Blog
Development of a data warehouse, ETL, data migration or conversion always faces an ever-decreasing timeline. These implementations can take years to complete and users are not ready to wait that long.
The waterfall development model has been discarded in favor of the agile or development model. However, this has changed only one component of the Data Development Life Cycle. This does not mean that the quality of these processes or the data they produce is of high quality.
How to Test an ETL Process | Blog
A source table has an individual and corporate customer. The requirement is that an ETL process should take the corporate customers only and populate the data in a target table. The test cases required to validate the ETL process by reconciling the source (input) and target (Output) data. The transformation rule also specifies that output should only have corporate customers.
iCEDQ Platform vs Data Quality Tools | Blog
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.
iCEDQ your Gatekeeper for Data Issues | Blog
The Challenges: Today’s organizations have thousands of data integration (ETL) processes constantly moving silos of data from various operational and/or external data sources to downstream applications.
Since the downstream system doesn’t have control over incoming data or the process, it can cause serious data issues due to:
The quality of the data depends on the upstream systems,
The ETL jobs may not process the data correctly.