DevOps was started more than a decade ago as a movement, not a product or solution category. DevOps offered us a way of collaborating between development and operations teams, using automation and optimization practices to continually accelerate the release of code, measure everything, lower costs, and improve the quality of application delivery to meet customer needs.
Prepping for a sales kick-off puts the focus on an organization’s customers unlike any other event. There is no selling — or success — without understanding and fulfilling the needs of our prospects and customers. As our gathering in Nashville last month proved, Talend is laser-focused on meeting customers wherever they are in their data journey, with everything they need to solve their most pressing data management challenges.
Data Talks fills a gap in the sports market by giving brands the data they need to truly understand their customers. But when your platform is responsible for continued ticket, merchandise, and sponsorship revenue, it needs to deliver insights fast. Here’s how Data Talks delivers data quickly with a rapid insights platform powered by Snowflake. From football fans filling out stadiums to baseball followers streaming every game, few customers are as avid and loyal as sports fans.
As organizations run more data applications and pipelines in the cloud, they look for ways to avoid the hidden costs of cloud adoption and migration. Teams seek to maximize business results through cost visibility, forecast accuracy, and financial predictability. Watch the breakout session video from Data Teams Summit and see how organizations apply agile and lean principles using the FinOps framework to boost efficiency, productivity, and innovation. Transcript available below.
As DataOps moves along the maturity curve, many organizations are deciphering how to best balance the success of running critical jobs with optimized time and cost governance. Watch the fireside chat from Data Teams Summit where Mark Sear, Head of Data Platform Optimization for Maersk, shares how his team is driving towards enabling strong engineering practices, design tenets, and culture at one of the largest shipping and logistics companies in the world.
Once in a while I stumble upon Spark code that looks like it has been written by a Java developer and it never fails to make me wince because it is a missed opportunity to write elegant and efficient code: it is verbose, difficult to read, and full of distributed processing anti-patterns. One such occurrence happened a few weeks ago when one of my colleagues was trying to make some churn analysis code downloaded from GitHub work.
