Click to learn more about author Josh Good. Shifting to the cloud helped countless businesses keep the lights on in 2020, as widespread disruption gave them the means and motive to fully embrace Software-as-a-Service (SaaS) across their business. Cloud services are now serving as the foundation for how enterprises adopt products and services, including analytics solutions. For those watching the market, it is clear that Gartner is right that public cloud services…

Click to learn more about author Scott Reed. Building an accurate, fast, and performant model founded upon strong Data Quality standards is no easy task. Taking the model into production with governance workflows and monitoring for sustainability is even more challenging. Finally, ensuring the model is explainable, transparent, and fair based on your organization’s ethics and values is the most difficult aspect of trusted AI. We have identified three pillars…

Click to learn more about author Thomas Hazel. Security analysts have long been challenged to keep up with growing volumes of increasingly sophisticated cyberattacks, but their struggles have recently grown more acute. Only 46% of security operations leaders are satisfied with their team’s ability to detect threats, and 82% of decision-makers report that their responses to threats are mostly or completely reactive – a shortcoming they’d like to overcome. The reactive approach…

Click to learn more about author Mathias Golombek. Is data mesh architecture the right approach for your organization and its data democratization journey? In my recent blog series, I delved into one of 2021’s hottest data topics – data democratization – exploring how it can fit into a business’ overarching data strategy along with some practical advice on how to implement data democratization in your own organization.  For today’s follow-up, I’m introducing another contemporary data concept: the data mesh. I’ll explore the link between…