Automating Data Validation with Pelican’s Zero Factor Features

Validating the migrated data is an equally important step in every migration process. Any successful migration project is not completed before the validation stage. And with the growing reliance on cloud-based systems, the need for data validation post-migration is becoming substantially high — it helps businesses in preserving data quality and eliminating costly errors or downtime.

Any inaccuracies or inconsistencies in the data after migration have a substantial influence on the organization’s operations and decision-making. To avoid such severe consequences, a thorough data validation process is crucial to assure the data’s reliability and dependability. But many organizations still rely on the age-old traditional methods of data validation that are inefficient, prone to errors, and require a lot of time depending on the volume of data.

The traditional method of data validation is inefficient

Migrating to the cloud significantly increases the volume and complexity of data, making manual validation even more challenging and time-consuming. Traditional or manual data validation consists of a series of steps:

• Consider data from Table A on the source system (eg: Oracle) is migrated to Table A+ on the target system (eg: BigQuery). The conventional method for validating data involves transferring Table A (from the source system) to BigQuery and comparing it with Table A+ in BigQuery (in the target system). However, this approach has some drawbacks that must be considered:
• Moving data across the network can be time-consuming and incur additional network costs. Secondly, in Big Query, Table A and Table A+ would each require the same volume of storage space, effectively doubling the storage costs. Due to the fact that BigQuery charges by the amount of data queried for a table, running multiple queries on both tables (A and A+) would incur additional costs, which could quickly accumulate.

Last but not least, the manual validation process involves dependencies on experienced SQL experts who are well-versed in writing the validation codes.

Enter Datametica’s Pelican

Datametica’s Pelican, the automated validation tool, automates data validation seamlessly with its Zero Factor features. Pelican can validate data accurately regardless of the volume of data to be migrated and the source and target systems. The zero factor features refer to a set of benefits that organizations observe when using Pelican. The features include:

• Zero Code Requirement
• Zero Data Movement
• Zero Downtime of systems
• High Data Security due to Zero Data Movement
• Zero uncertainty when decommissioning legacy systems.

⚠️ [NEWS]: Pelican is available for users on the Google Cloud Platform Marketplace from 27th April 2023!

How do Pelican’s Zero Factor features make it easier to do data validation?

In Pelican, data validation is approached somewhat differently. Table A remains in the source system (Oracle), while Table A+ remains in the target system (BigQuery) – which is why it features zero data movement. Pelican employs a pushdown architecture, which utilizes the processing power of the source and target data platforms to perform validation.

Pelican selects data from the source and generates a fingerprint of that data using a proprietary algorithm in order to validate the data. This fingerprint is then folded to an extremely minimal level, reducing gigabytes of data to a few megabytes. Pelican can also traverse the folder structure and identify mismatched samples, allowing for a more thorough validation of the data.

Using the same algorithm, Pelican selects data from the target and generates a fingerprint using the same procedure. This produces a very small footprint from both source and target, which is then compared to the Pelican machine. Pelican is able to perform data validation with minimal impact (i.e. zero downtime) on both the source and target data platforms by employing a pushdown architecture and a proprietary algorithm. This method not only reduces network and storage costs but also enables more thorough data validation, including the capability to identify and compare mismatched samples.

Pelican’s intuitive and simple UI makes it easy for testers to simply validate the source system data with the target system data without having to do a single line of code manually – which is why Pelican has zero code requirement.

Pelican’s cell-level data validation features boost the confidence of 100% migrated data accuracy, resulting in zero uncertainty while decommissioning the legacy systems.

Suggested read: Automating Test Management & Validation Process Management for a Successful Cloud Migration