All About ETL Testing, Data Migration & Data Warehouse Testing

Data Centric Testing

A Practical Guide for Data Centric Testing: Automated ETL Testing

“Information is the oil of the 21st century, and analytics is the combustion engine”- Peter Sondergaard, Senior Vice President, Gartner Big Data and Business Intelligence are becoming an increasingly important source of statistical information which is used as a vital part of the critical decision-making process of all businesses. Bernard Marr, in his article titled…

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iCEDQ DataOps Platform.

AML Software Implementation & Production Monitoring with iCEDQ DataOps Platform

iCEDQ accelerates AML software implementation and prevent false positive signals in AML operations. 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…

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Guard for Data Issues

iCEDQ your Gatekeeper for Data Issues

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…

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Data Factory Challenges

What Are The Challenges Of A Data Factory

DataOps Platform for Integrated Data Testing & Production Monitoring. DataOps is a set of practices and tools used by Big Data teams to increase velocity, reliability, and quality of data analytics. It emphasizes communication, collaboration, integration, automation, measurement and cooperation between data scientists, analysts, data/ETL (extract, transform, load) engineers, information technology (IT), and quality assurance/governance.…

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Test Driven Development

QA Challenges in Data Integration Projects

  Download Whitepaper from here QA Challenges Data Integration Projects Quality Assurance (QA) is a very important component of any data-centric application project.  Projects such as data warehouse, data migration, ETL, Data Lakes and MDM are no exception. The Majority of these projects are the multi-year and multi-million dollar in nature due to the amount of…

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iCEDQ Agile Way

Agile Data Warehouse Testing & Data Migration Testing

Automate data warehouse etl testing and migration testing the agile way from Sandesh Gawande   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…

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Data Migration Process

The Data Migration Process & the Potential Risks

What is Data Migration? Data migration is the process of transferring data from one system to another system, known as the target system, using a variety of tools and techniques. Below are the different types of migrations which are encountered in different enterprises: Database Migration: This involves moving from one database software to another. E.g.…

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3 Reason TO Perform ETL Testing

3 Reasons Why You Need to Perform ETL Testing

An ETL process is at the heart of any data centric system/ project be it Data Migration or Data Warehouse. All the data movement, transformation, and conversions are done by the ETL process in order to ensure that all the data is uniform in terms of quantity, quality, and format. So, why is ETL testing…

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iCEDQ vs Other Tool

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…

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How to test an ETL Process – Basic Concept

The basic concept of ETL Testing and Data Warehouse Testing The answer lies in the understanding of an ETL process. An ETL process at its core reads data, applies a transformation on it and then loads the data. This can be represented by the following simplistic equation. Input Data + Transformation = Output Data The…

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ETL Testing Vs. Application

ETL Testing Vs. Application Testing – The Fundamental Difference

At the core, quality is the measurement of deviation between what is expected vs. actual. In quality assurance practice, we implement a set of tests to measure this deviation. The extent of the deviation indicates the quality of the software. In any application testing, there are three common terms that we will notice: Requirements Test…

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ETL Testing and Data Quality

ETL Testing and Data Quality Governance Software – The Missing Link

Data has become critical to 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 There…

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