The State of Data Science in 2020

Companies that develop or support products in the field need to transition from reactive to predictive maintenance and service. Such a transition is possible using ubiquitous connectivity and predictive analytics on machine data. Here’s how.

Although edge architectures differ fundamentally from conventional cloud and on-premises environments, edge isn’t an alternative to traditional infrastructure strategies as much as it is an augmentation of them.

The relationships banks have with their customers can last for decades, but too many banks fail to use the data they have to provide personalized digital banking services. 

Every transaction, order, customer interaction, and internal operation depends on decisions. At a time when businesses are under pressure to improve efficiencies, cut costs, and be more responsive, automating decisions becomes essential. While many businesses have picked off the low-hanging fruit when automating, most need to add more. Specifically, businesses want to automate complex decisions, involving multiple steps, multiple data sources and many rules.

Zero Trust assumes a strong, unified source of identity and policy. Most enterprises have the opposite. Create a cross-functional “Zero Trust Council” with shared KPIs tied to business outcomes to fix the situation.

Organizations that align their data strategies with 2026 cloud evolution trends will be well-positioned for success in the modern AI-dominated business world.

Enterprise leaders call on providers to address the automation gap between enterprise IT systems and service provider networks.

Building a Shared Responsibility Model into a company’s long-term strategy is a critical part of running successful operations.