Although this demonstration was from several years go, it is still relevant today. And in fact, Atlassian’s expanded tool suite have only been more tightly integrated! Atlassian’s tools ensure they work well together, achieving a seamless integration of ticket and tracking systems, continuous integration servers and repository management systems.
Back in 2014, we hosted Jens Schumacher, then the group product manager for Atlassian’s development tools in Sydney for a few days. We captured this demonstration where he showed us how Jira, Stash and Bamboo work together – from issues to branches, pull requests and tests, to a successful quality-checked release of a change made to the main code base.
Let’s have a look at how Atlassian’s tools were integrated all those years ago!
Google Docs has built-in collaboration options, such as those that allow people to simultaneously make real-time edits to documents.
However, even though the tool is feature-rich on its own, it’s still possible to get even more from Google Docs by going beyond its handy built-in features and using some third-party add-ons.
Here are six that should boost collaboration among teams.
In addition to an introduction, we believe it would be useful to actively exchange information with the existing community. So, last November we organized a community and user meetup for ERPNext at our head office in Wiesbaden, and were delighted to host Rushabh Mehta, the founder of ERPNext.
At //SEIBERT/MEDIA we have introduced an adapted version of the Decision Tree model by Susan Scott to make decision structures in a complex environment more transparent and straightforward. But how does it work in practice? This post looks at the model in practice using the development of our social intranet suit Linchpin as an example.
We want to take this opportunity to thank all of our customers, partners, event staff, colleagues, guests – everyone we have had the pleasure of working with or helping this year! We’ve had a fantastic year with Linchpin, draw.io, Agile Hive, G Suite, our Tools4AgileTeams conference, our regular breakfast information sessions, teaching kids how to program with programmieren.de, the Atlassian Summit in Barcelona, and all of the other events we both attended and hosted.
As our organization grows and projects become more complex, we have noticed the need for more structure when it comes to decision making. In this post, we consider the Decision Tree model by Susan Scott (2000) and how it could be applied in our organization.
Do you want your intranet to be understood and to be used intuitively by all your employees, even by technically inexperienced users ? A clear design, one that feels relevant, with a smooth start up and an intuitive user interface are important aspects. Linchpin achieves this and more by limiting the complexity of Confluence, adding opportunities for personalization across the board, extensive design options and seamless interaction between Linchpin apps – with easy-to-use administration functions and no fuss.
Navigation menus are an important requirement for customers who use corporate intranets. However, the standard version of Confluence doesn’t offer many options that give you control over your navigation menus. This is where the Linchpin Navigation Menus app (previously called the Navigation Menu Editor) comes into play. It adds this much-needed functionality to Confluence, and along with the other central components of the Linchpin intranet suite, it extends Confluence to be a complete corporate intranet.
We are a closely-knit team at //SEIBERT/MEDIA, and we enjoy spending time together during various events and have also established a number of different company sports groups for a healthy balance – from soccer to yoga, to badminton. I will introduce you to some of them in this post!
Many businesses choose cloud data warehouse services, like Amazon Redshift, Google BigQuery, etc. to analyze their data, as they offer high scalability and on-demand computing power and are supported by a large number of various data analysis tools. Let’s consider a more specific case when there is a need to analyze company data from a Jira system, and Google BigQuery is selected as a data warehouse for analysis. There can be different ways to solve this scenario – build vs. buy.