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Businesses must be prepared to handle unexpected disruptions, whether due to natural disasters, cyberattacks, or system failures. Disaster recovery (DR) planning is essential for ensuring business continuity and minimizing the impact of these disruptions.   This blog is a follow-up to our blog on data resilience with actionable insights for Oracle Cloud Infrastructure (OCI). Within OCI organizations have access to a

Data sharding is a database architecture pattern that involves splitting a large database into smaller, more manageable pieces called shards. Each shard is a subset of the database that holds a portion of the data. This technique is particularly useful for enhancing performance, scalability, and reliability in large-scale database systems. Explore the role of sharding on NoSQL databases in our

The link between strong database performance and business operations is undeniable. Efficient SQL queries are crucial for ensuring fast data retrieval and overall system performance. From advanced SQL query optimization techniques, to indexing strategies, query rewriting, and understanding execution plans, this blog post aims to equip you with insights for improved SQL Server performance.  Enhance your understanding and ability to

We are thrilled to celebrate a remarkable milestone as we honor Greg Mays for 25 years of dedicated service. As the Oracle Practice Lead, Greg has been an integral part of our team, contributing significantly to our growth and success.   Since 1999, Greg’s commitment to excellence and his passion for technology have been evident in every project he undertakes.

Ensuring the optimal performance and reliability of your Oracle Cloud Infrastructure (OCI) environment is crucial for maintaining the health and efficiency of your applications and services. Effective monitoring and observability are key components in achieving this goal.   This article explores the tools and techniques available in OCI to help you monitor your resources and gain valuable insights into your infrastructure.

Author: John Whitehead, VP of Data Services With the rise of generative AI, IT professionals have increasingly explored potential benefits and drawbacks associated with harnessing these tools. The following article provides a comprehensive overview of GitHub Copilot with careful consideration given to the overarching impact of generative AI on the field of database management. Additionally, gain expert insights from developers

Data wrangling, also known as data munging, is the process of cleaning, transforming, and organizing raw data into a usable format for analysis. It involves various tasks such as removing inaccuracies, filling in missing values, and reformatting data to help make it consistent and prepared for advanced analytics. High-quality data is the foundation for reliable insights and informed decision-making. Data

In the realm of data management, ensuring compliance with regulatory standards can often feel daunting. Database compliance audits play a crucial role in verifying that organizations adhere to stringent guidelines surrounding identifying gaps, mitigating risks, and demonstrating accountability.  This blog will delve into the significance of database compliance audits, their key components, practical considerations for conducting them, and the tools

Implementing data masking for privacy protection in databases can help to safeguard sensitive information. Specifically, this strategy involves creating a version of data that looks structurally similar but hides sensitive information, ensuring that unauthorized users can’t access real data.   Begin by identifying the sensitive data in your database. Common examples we regularly work to protect against threats include: personal identifiable