I often get asked why Yellowfin decided to go global. While the Australian market is relatively large, it’s also quite risk averse, which makes it a challenging market to sell into. While VC-backed software vendors have the benefit of selling to others within their VC family, as a bootstrapped startup we had to forge legitimate markets outside of Australia. We knew that we had to spread our wings to grow and expanding overseas quickly gave us the opportunity to sell faster.

Recently, I read why companies are failing in their efforts to become data-driven in the Harvard Business Review. It said that 72% of Chief Data Officers believe their organization doesn't have a data culture and 92.5% of them blame their people. But I think they’re wrong. The real issue is that people aren’t using the tools that their CDOs have bought for them. That means the problem isn’t with the users, it’s with the technology they’ve been given.

I recently had the pleasure of attending the Center for Business Analytics Career Panel event at Villanova University where myself and other analytics professionals sat on a panel to discuss the future of analytics with the students.

Back in the 60s Bod Dylan sang “The Times They Are a-Changin” which has become a famous and lasting anthem of change. Bowie wrote ‘Changes’ in the 70s but it’s the “Winds of Change” from the Scorpions that plays in my head when I hear the phrase - Change is the only constant, and nowhere is this truer than in the world of tech.

By now, you know that data is the lifeblood of digital transformation. But the true digital leaders have taken a step beyond by starting to understand the need to preserve this lifeblood with people, process and tools. That’s why data quality is so important in its ability to take control of the health of your data assets from diagnostic to treatment and monitoring with whistleblowers.

Let me start by thanking all those who read the first part of our blog series on converting legacy ETL to modern ETL! Before I begin the second part of this three-blog series, let’s recap the three key aspects under consideration for converting from legacy ETL to modern ETL.

There’s recently been an important debate taking place on LinkedIn around the topic of relational databases, joins and how that impacts a user’s experience with analytics.

Almost three years ago today, to the day, Talend opened its fourth global research and development center, and its second one in France, in Nantes. It was clear to Talend from the very beginning of this new innovation center that it would not be a simple satellite of existing centers, but a key element in our strategy and overall R&D efforts.

As analytics software vendors, we need to do something profoundly different to improve how business users access, consume, and interact with data.

When doing data matching with large sets of data, consideration should be given to the combinations that can be generated, and it’s associated effects on performance. This has an effect when using Talend’s Data Integration Matching and Data Quality components. Matching routines do not scale in a linear fashion.