If “necessity is the mother of invention,” COVID-19 forced many businesses around the world to rethink their digital transformation, data and analytics strategies. Out of every crisis, there will be opportunities. Although the current pandemic has certainly acted as a black swan event in some cases impeding progress, it has, nonetheless, accelerated several of the trends already pushing toward a digital future.

“Build vs Buy” is an important decision every technology strategist has to make. With the rise of open source and the wealth of freely available software, organizations have the flexibility to build custom solutions when off-the-shelf solutions don’t directly address their needs. In the domain of enterprise data platforms, many organizations have leveraged the open-source ecosystem to build tailored solutions, expending a lot of resources in the process.

We are happy to announce Talend is a Leader in The Forrester Wave™: Enterprise Data Fabric, Q2 2020. Talend’s unified approach to data management – combining data integration, integrity, and governance in a single platform – is the best way to gain clarity and confidence in your data. Since we launched Talend Data Fabric in 2015, we’ve been strong believers that data integration and management could not be solved with a static, siloed enterprise software solution.

One of the most interesting developments coming out of the current COVID-19 crisis is that people are looking at and interpreting data like never before. People that have never expressed an interest in data are now thinking about data and trying to understand what it means for them. There is a lot that businesses can learn from this. With COVID-19, people are taking the time to look at highly complex data, distill it, and assess what it means for their own behavior and lives.

Qlik is excited to announce the June 2020 product release, furthering our leadership in augmented intelligence, best-in-class visualization and platform extensibility.

Even in a global economy, businesses need a deep understanding of local markets. For example, marketing campaigns designed to attract buyers in a large metropolitan area won’t necessarily attract small-town customers. Noticing that buying patterns in one area are extending into a larger regional or nationwide trend can lead to decisions that increase profits. But accessing and analyzing a broad spectrum of geospatial data has been difficult and expensive. That is changing.