In HeathTech apps, it’s often the case that you’re dealing with private or health-related data. This requires compliance with regulations, such as HIPAA in the United States. These regulations force you to handle sensitive data in a well-defined manner, so only specific people can read it, and if they do, it should be logged for later auditing.

Here at Ably, we deal with hard engineering problems all the time and pushing at the edges often results in us running up against all sorts of interesting gotchas. We recently made some AWS NLBs fall over, and had a hazardous encounter with Cassandra counter columns. In our day-to-day, we use gRPC for fast and efficient data exchange with mutual client/server state synchronization.

Russell Stephens from Compass shares how his team cut down the time spent on testing from 80 hours to 4 and shortened their release cycles to one week. Read on to find out what steps they took to achieve this!

Businesses hoping to make timely, data-driven decisions know that the value of their data may degrade over time and can be perishable. This has created a growing demand to analyze and build insights from data the moment it becomes available, in real-time.

Many agencies that handle mission-critical functions still rely on outdated and legacy software applications that have evolved into complex and costly solutions over time. These legacy systems sit at the heart of daily business operations—and have a negative impact on efficiencies, stakeholder satisfaction, and overall mission outcomes. While most stakeholders agree that modernization is needed, they also know it’s a complicated undertaking.

Businesses large and small depend on access to information in order to make smarter, data-driven decisions. And much of that data is personal, sensitive, or confidential. So how can you balance this demand for big data with the need to protect the individuals whom this data describes? When it comes to personally identifiable information (PII), there are multiple very good reasons why you should keep it securely under lock and key.

What do Xplenty, Snowflake software, and dbt (data build tool) have in common? When used together, they merge the best of ETL (extract, transform, load) and ELT (extract, load, transform) into a powerful, flexible and cost-effective ETLT (extract, transform, load, transform) strategy. In this guide, we’ll show you how to create an ETLT strategy with Xplenty, Snowflake software, and dbt. But first, we’ll explain why you'd want to use this strategy to build an ETLT data transformation stack.

DreamFactory specialises in REST API generation for any number of database types however an underrepresented benefit is the ability to mount and manage any third party API via a HTTP service connector. This gives you the ability to generate documentation and secure an existing API as if it were created natively within DreamFactory.

DreamFactory specialises in REST API generation for any number of database types however an underrepresented benefit is the ability to mount and manage any third party API via a HTTP service connector. This gives you the ability to generate documentation and secure an existing API as if it were created natively within DreamFactory.

“Talend is amazing because it’s open, flexible, and visual. The robustness and reliability of Talend have made it an integral part of our solution set. It’s easy to learn and fast to ramp up.” – Jason Vogel, IT Manager, AutoZone AutoZone is America’s #1 vehicle solutions provider. It was founded in 1979 and has since expanded to more than 6,400 stores across three countries, with over 96,000 employees.