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How to Successfully Manage a File Migration

Pure Storage

Discovery: Know Your Data Inside and Out Before diving headfirst into the migration process, it’s absolutely essential to have a clear understanding of your data. Data integrity is paramount. This includes ensuring data integrity, checking permissions, validating application integrations, and more.

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OLAP vs. OLTP: Comparing Data Processing Systems

Pure Storage

These systems provide a systematic way to store, organize, and access information, allowing users to efficiently interact with and manipulate data for various purposes, such as analysis, reporting, and application development.

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Data Resilience: The Key to AI and Cybersecurity

Solutions Review

While AI and cybersecurity continue to dominate news headlines, one critical aspect of digital infrastructure is often overlooked: data resilience. By providing continuous availability and data integrity, data resilience reduces the risks of data loss and downtime, building the foundation for the dependability of these advanced systems.

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Unveiling the Importance of Power BI Backup: Safeguarding Your Data’s Future

Zerto

In today’s data-driven business landscape, Microsoft Power BI has emerged as a critical tool for organizations to analyze and visualize their data, derive insights, and make informed decisions. However, ensuring the availability and integrity of this valuable data is paramount. Compliance and data governance.

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The State of DR and Cyber Recovery – Part 3: Choosing the Right Disaster Recovery Solution

Zerto

In part-1 , we looked at the top reasons for data loss and some ways to address them, while in part-2 we focused on the top disaster recovery challenges faced by organizations. Granular data recovery means minimal data loss, especially when using continuous data protection capabilities that deliver an RPO measured in seconds.

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Denormalized vs. Normalized Data

Pure Storage

Denormalization involves combining tables that have been normalized to improve query performance and simplify data retrieval. The choice between the two depends on the specific requirements of the application and the balance between data consistency and system performance, but both play a very important role in data management.

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ETL vs. ELT

Pure Storage

Malformed data might be discarded, or developer scripts might try to salvage some malformed data and store it as a partial record. What you do with data depends on your business requirements. Without ETL, relational databases might reject malformed data and important information could be lost.