Let’s get this out of the way: To understand the much discussed ’death of the dashboard' proclamation, the phrase needs to be viewed under a different lens beyond the literal. Firstly, it's not a new concept at all: Yellowfin have been saying it for years. The problem is in the current confusing interpretation around what it means for business intelligence. In short, dashboards aren’t actually dying, nor is their usefulness for certain users spent.

In this episode of CDO Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Meenal Iyer, Sr. Director of Enterprise Analytics and Data at Tailored Brands. They discuss battlescars in two areas, data and metrics: Growing Data Literacy and Developing a Data-Driven Culture and Standardization of Business Metrics.

There is a lot of talk these days about the dashboard being a thing of the past. After all, simply displaying KPIs and visualizations in a dashboard is something everyone can do, right? If monitoring KPIs is all you need to do, then we would agree: The dashboard is largely dead. We can deliver those singular data points to you anywhere, monitoring what you’re interested in, alerting you to changes and triggering action.

In their quest to find out if Keboola could be of wider benefit to a company that has so far been using the platform only as their ETL solution, Michal Hruska, a senior data consultant at Keboola, and Pavel Dolezal, Keboola’s CEO, met with Tim, the company’s data analyst. They sat down to talk about the beaten tracks of working with data and its challenges and the ways Keboola can help solve them.

Here’s how to choose a relational database for your next project.

k6 v0.31.0 is here! 🎉 It's a smaller release with some significant performance improvements, as well as some really exciting new features. For additionall details, see the full release notes on GitHub.

Regardless of the tech stack used, many developers have already used Redis or, at least, heard of it. Redis is specifically known for providing distributed caching mechanisms for cluster-based applications. While this is true, it’s not its only purpose. Redis is a powerful and versatile in-memory database. Powerful because it is incredibly super fast. Versatile because it can handle caching, database-like features, session management, real-time analytics, event streaming, etc.

Since the beginning of time, back to before humans invented fire, there were two traditional ways to debug applications: one way -after having invented hieroglyphics, of course - was by reading log lines and the other was by using the common debuggers that surrounded a cave dev’s cave. It’s safe to say that society has progressed since then and, luckily, so too has traditional debugging.

In a previous post, C++ Microservices in Docker, we worked through the steps for creating a docker container that exposes a HydraExpress servlet container. We successfully deployed our HydraExpress server instance in Docker, however all that was available were the default example servlets. User application code wasn’t exposed. Let’s fix that and look at deploying custom C++ Servlet instances within the HydraExpress Docker container.

Companies these days are handling more data than ever: an average of 163 terabytes (163,000 gigabytes), according to a survey by IDG. Efficiently storing, processing and analyzing this data is essential in order to glean valuable insights and make informed business decisions. Yet the question remains: What is the best way to store enterprise data? For many use cases, the most appealing choice is a relational database.