In every home, there is a place that we store things that we no longer need or use. It’s something that once gave us joy, albeit at an initial cost, and for this reason we seem unable to throw it away even though we no longer have a use for it. The main culprit? Old tech gadgets. Whether it’s at my home, my parent’s house, or the family holiday house, there is always a drawer where old phones, cables, music players, and earphones are stored away and forgotten about.

If you're a developer trying to ETL data into and out of Heroku, the seemingly shortlist of options may disappoint you. Heroku itself promotes Heroku Connect, but this expensive solution might not even integrate with all the systems you use (like AdWords and Facebook), making it difficult to get a holistic view of your data. Fortunately, Heroku Connect isn't the only solution. In fact, there are several third-party ETL tools that can help you get your data in and out of Heroku with ease.

One of the key pieces of work that we've done this past year is to actually build a completely bespoke application, so that we could properly look at the different ways that we could embed Yellowfin. This has helped us create a really unique customer experience within a third-party application. Like all great stories, our vision fundamentally changed on that journey, and we learned three valuable lessons as we built this application we want to share with you.

As a result of overwhelming excitement (and pressure) from my fellow Qlikkies, I’m going to share with you the recent demo I did at our all-company annual kick-off which shows Active Intelligence in action. It was intended to be an “internal-only” demo because it mixes existing capabilities with near-term future ones, but, on reflection, I think you, too, will be just as excited.

Event management is at the heart of the trend of virtual events. Whether it is online trade shows, webinars, or live-streamed conferences & performances, everything is possible nowadays thanks to the latest technology. However, for hosting a successful virtual event, you need to opt for the right tech tools. With the help of these tools, you can drive registrations and engagement and run the event without any hassle.

If you have been keeping track, I recently started a series of blog posts about the state of developer tooling in the Kubernetes ecosystem in 2021. The first blog post covered the topic of defining Kubernetes applications, i.e., how you go about declaring, packaging, customizing, and deploying them. You can check out that up to date comparison between category leaders Helm and Kustomize right here.

About two decades ago, testing was only limited to the desktop. With the rapidly increasing use of smartphones and ease of access to the internet across the globe, testing has spread across vast platforms. The native and mobile web browser testing is being performed more and more compared to desktop testing.

The meteoric emergence of smartphones is nothing short of phenomenal, as a growing number of consumers are leveraging the potential offered by the smartphone ecosystem. As per April 2019 data of Statistica[1], the global mobile population accounted for 4 billion unique users. That’s not all, the global mobile traffic is expected to increase sevenfold between 2017 and 2022. The daily media consumption on mobile devices has grown by 504 percent since 2011[2].

There is a scene in a certain TV show in which a middle-aged man tells a younger one that he missed picking someone up from the train station because his device did not remind him about it. The younger man points out that, since he bought a new device, he must transfer the appointments.

Manufacturing’s digital transformation growth is truly impressive considering it’s delivering value with explosive growth rates. Consider that Manufacturing’s Industry Internet of Things (IIOT) was valued at $161b with an impressive 25% growth rate, or that the Connected Car market will be valued at $225b by 2027 with a 17% growth rate. But then conflicting information arrives as VentureBeat reports that around 90 percent of machine learning models never make it into production?