All About ETL Testing, Data Migration & Data Warehouse Testing

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Migrating Database to Redshift, Snowflake, Azure DW and Test with iCEDQ

Migrating Database to Redshift, Snowflake, Azure DW | Blog

The complexity of migration from a database to a new platform and time for implementing it has many challenges; Lack of strategy, incorrect assumptions, lack of tools, and complexity of the environment to name a few.

We at iCEDQ are not involved in choosing your new database platform. Choosing a database platform is beyond the scope of this article. We do want to help you by providing a checklist for your data migration effort and a data migration testing strategy.

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Overcome Data Testing Challenges Featured Image - iCEDQ

Overcome Data Testing Challenges | Blog

Today all decisions in an organization are being made on the data available to them. Hence it has become critical to ensure that the data is free of any issues or defects. The way to ensure that there are no data issues and it is fit for the business, is to test, validate and compare it regularly.

Some of these organizations are either testing the data manually or not testing at all. We all are aware of the issues and challenges of testing anything manually but data testing has its own set of unique challenges on top of that. Below are some of the data testing challenges every organization encounters. The challenges mentioned below are for data testing which translates into Big Data Testing, ETL Testing, Data Migration Testing and few others.

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A Practical Guide for Data Centric Testing Automated ETL Testing - iCEDQ

Practical Guide for Data Centric Testing | Blog

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 “4 Ways Big Data Will Change Every Business” reiterates the industry-belief that “big data and its implications will affect every single business -from Fortune 500 enterprises to mom and pop companies – and change how we do business, inside and out.

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QA Challenges in Data Integration Projects Featured - iCEDQ

QA Challenges in Data Integration Projects | Blog

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 work and products required. Therefore it’s necessary to have proper planning for QA in place to avoid late discoveries of process and data errors.

While the methodologies of testing have evolved considerably over the years, the science of QA in data integration project has not. In this article, we’ll focus on some of the key challenges with data warehouse testing, data migration testing and ETL testing.

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The Data Migration Process & the Potential Risks Feature - iCEDQ

The Data Migration Process & Potential Risks | Blog

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. your organization just bought HP Vertica and is planning to from MySQL to HP Vertica. Database Version Upgrade: This involves upgrading the older version of the database to the latest or most current available database version.

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What Are The Challenges Of A Data Factory - iCEDQ

Challenges Of A Data Factory | Blog

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. It aims to help organizations rapidly produce insight, turn that insight into operational tools, and continuously improve analytic operations and performance.

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What is BI Testing and the Importance of BI Report Testing - iCEDQ

BI Testing & Importance of BI Report Testing | Blog

Reports and dashboards are extensively used to make business decisions. These decisions later form the basis for the company’s growth and success. If BI reports are wrong, then decisions taken based on these reports will also be wrong. Inaccurate reports affect the organization’s credibility and also exposes them to compliance and legal issues. It can also lead to hefty fines that organizations can not afford to ignore BI Testing.

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