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3 Reasons Extract, Load & Transform is a Bad Idea

Extract, Load, Transform (ELT) technology makes it easy for organizations to pull data from databases, applications, and other sources, and move it into a data lake. But companies pay for this convenience in many ways. ELT solutions can have a negative impact on data privacy, data quality, and data management.

Building a Single Pipeline for Data Integration and ML with Azure Synapse Analytics and Iguazio

Across organizations large and small, ML teams are still faced with data silos that slow down or halt innovation. Read on to learn about how enterprises are tackling these challenges, by integrating with any data types to create a single end-to-end pipeline and rapidly run AI/ML with Azure Synapse Analytics with Iguazio.

Navigating the 8 fallacies of distributed computing

The fallacies of distributed computing are a list of 8 statements describing false assumptions that architects and developers involved with distributed systems might make (but should undoubtedly steer away from). In this blog post, we’ll look at what these fallacies are, how they came to be, and how to navigate them in order to engineer dependable distributed systems.

Rails Security Threats: Authentication

Authentication is at the heart of most web development, yet it is difficult to get right. In this article, Diogo Souza discusses common security problems with authentication systems and how you can resolve them. Even if you never build an authentication system from scratch (you shouldn't), understanding these security concerns will help you make sure whatever authentication system you use is doing its job.

Getting By With A Little Help From My Visual Tracing

When working with Rookout customers, one of the most commonly heard requests we hear is a plea for “context”. When trying to debug a complex applications, setting a Non-Breaking Breakpoint and fetching a full view of local variables and stack trace is a necessary first step. But in a complex, distributed environment, this first step is not always enough.

BigQuery row-level security enables more granular access to data

Data security is an ongoing concern for anyone managing a data warehouse. Organizations need to control access to data, down to the granular level, for secure access to data both internally and externally. With the complexity of data platforms increasing day by day, it's become even more critical to identify and monitor access to sensitive data.