Many agencies that handle mission-critical functions still rely on outdated and legacy software applications that have evolved into complex and costly solutions over time.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.

Cloudera is trusted by regulated industries and Government organisations around the world to store and analyze petabytes of highly sensitive or confidential information about people, healthcare data, financial data or just proprietary information sensitive to the customer itself.

Companies today are faced with an analytics conundrum. On one hand, there’s a higher demand than ever for actionable business insights, but on the other there’s limited resources to deliver BI content to on-technical business end-users. To fill this gap, the industry is increasingly turning to the next generation of self-service analytics tools. These tools reduce time to insight, speed up insight to action, and also allow BI teams to focus on more strategic analytics work.

This tutorial will walk through a common use case for the Kong Gateway Key Authentication plugin: using API key authentication to protect a route to an API server endpoint. It’s a simple use case, but it will give you the foundation to deploy and configure the plugin for your own unique project needs. Before we walk through our mini-project, let’s cover a few core concepts.

One of the most powerful capabilities provided by Kong Konnect Enterprise is the support for Hybrid deployments. In other words, it implements distributed API Gateway Clusters with multiple instances running on several environments at the same time. Moreover, Kong Enterprise provides a new topology option, named Hybrid Mode, with a total separation of the Control Plane (CP) and Data Plane (DP).

This post tells a story of a performance mistake that is quickly made even by experienced developers: The expectation that a built-in PHP function has better performance than a better suited data structure written in PHP. The protagonist in these stories is array_unique, a function that takes a list of values and removes duplicate entries to return a list of each value occurring only once.