As we covered in part 1 of this blog series, Snowflake’s platform is architecturally different from almost every traditional database system and cloud data warehouse. Snowflake has completely separate compute and storage, and both tiers of the platform are near instantly elastic. The need to do advanced resource planning, agonize over workload schedules, and prevent new workloads on the system due to the fear of disk and CPU limitations just go away with Snowflake.

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.

As a product feature for your app, embedded analytics is undoubtedly a valuable tool. But historically, many product managers and software developers have approached it as a standalone capability. This has led to dashboards and reporting modules added as an afterthought, rather than as a founding strategic component of the core application.

The customer has never been more right. Across industries, customers have become conditioned to demand not only near-instant responses to their needs but that their needs be anticipated in advance. Financial institutions are not given a pass, despite a competitive landscape flooded with regulation and privacy considerations. The customer still has expectations for a personalized, timely, and relevant experience.

The push to embrace cloud-based technologies has undoubtedly transformed IT infrastructures at every level of government. Federal, state, and local agencies have made significant strides in modernizing how data is collected, stored, and analyzed, all in service of their mission and in fulfillment of strategic IT mandates.