Recently, Databricks introduced Delta Lake, a new analytics platform that combines the best elements of data lakes and data warehouses in a paradigm it calls a “lakehouse.” Delta Lake expands the breadth and depth of use cases that Databricks customers can enjoy. Databricks provides a unified analytics platform that provides robust support for use cases ranging from simple reporting to complex data warehousing to real-time machine learning.

With Yellowfin 9, we introduced to the world an incredibly flexible, action-based dashboard builder and progressive data storytelling capabilities that advance the capability of the dashboard experience. We’ve received great feedback since then and this month, the newly-released 9.1 further enhances the user experience of analysts, developers, and business users in Yellowfin’s action-based dashboards, data storytelling, and data discovery products.

The principles behind performance testing API’s does not differ from the principles behind the performance testing of any application. Many API’s however are Asynchronous and a valid response from the API does not necessarily mean the transaction is complete which can cause a problem when measuring the performance of API’s. There are however ways around this and we will explore these in this post.

How can we bridge the gap between business and development? How do we make sure that features being developed are according to the business requirements from the beginning? The answer is BDD, a framework that allows the business requirements to be converted into test cases that are reviewable by business and users when needed. Let us start with understanding what is Behavior Driven Development and the purpose it serves in detail below.

April 7th, 2020 • By Jon de Andrés Frías In the first part of our series of blog posts on how we remove technical debt using Apache Kafka at Rollbar, we covered some important topics such as: In the second part of the series, we’ll give an overview of how our Kafka consumer works, how we monitor it, and which deployment and release process we followed so we could replace an old system without any downtime.

Data saturation is everywhere. We want to collect more data because we want better information from them. However, the rapid rise in our ability to collect data hasn’t been matched by our ability to get meaningful insights from the data.