Read more about author Rahul Rastogi. In May, OpenAI announced a partnership with Reddit to train its language models using the forum’s extensive collection of user-generated content. OpenAI’s goal of enhancing its models’ ability to respond to real-world conversations and diverse linguistic patterns seemed straightforward. But the decision quickly sparked concerns – namely, the potential inclusion of misinformation and biased content in the training data, based on the unregulated nature of Reddit’s…

Read more about author Itamar Ben Hemo. Given that data is the lifeblood of modern enterprises, the specter of data breaches looms large. The 2024 Snowflake data breach sent shockwaves through the tech industry, serving as a stark reminder of the ever-present threats in data management. While the cause of the breach came down to a combination of an aggressive hacking campaign and poor security practices on the part of…

Read more about author Wayne Yaddow. Today’s data pipelines use transformations to convert raw data into meaningful insights. Yet, ensuring the accuracy and reliability of these transformations is no small feat – tools and methods to test the variety of data and transformation can be daunting.  Transformations generally involve changing raw data that has been cleansed and validated for use by individuals or systems. Data transformations are essential for data management, integration,…

Read more about author Oleksandr Sanin. In today’s virtual-first economic system, companies are under relentless strain to ensure their products deliver the most effective overall performance with minimal downtime. Whether it’s SaaS software serving thousands of customers globally, or a complex company platform assisting vital commercial enterprise functions, the call for reliability and efficiency is higher than ever. As IT infrastructures continue to grow in complexity, conventional strategies for dealing…