Business intelligence (BI) has gotten so sophisticated that a variety of end users within an organization may be eager to use data to guide their decisions. Unfortunately, most businesses have a very small data analysis or BI team. How can companies like this enable more people to use more data more effectively without overwhelming their BI staff?
The word “data” is ubiquitous in narratives of the modern world. And data, the thing itself, is vital to the functioning of that world. This blog discusses quantifications, types, and implications of data. If you’ve ever wondered how much data there is in the world, what types there are and what that means for AI and businesses, then keep reading!
In a Harvard Business Review article, Thomas C. Redman references a project by AT&T, the world’s largest telecommunications company, where the simple task of reducing invoicing errors uncovered something shocking: over 40% of invoicing data contained errors that cost the company tens of millions of dollars. Even in 2021—the age of digitalization—poor quality data is wreaking havoc in businesses, costing the United States a staggering $3 trillion per year.
Low-Code. This is a new term for many, and it raises questions. The first is “What is it?” Suffice to say, low-code is a new way to build software applications that is faster and better than traditional coding. A more urgent question is “why do we need it?” What kinds of shifts has the world seen that have caused something like low-code to gain prominence? We need to take a few steps back to understand how business and the tech industry have evolved.
Even when seamlessly combining manual and automated approaches, testing every functional combination within web or mobile applications is challenging. Unfortunately, this means critical issues inevitably go undetected and make their way into the hands of your customers. We strive for perfect code, perfect releases, and perfect apps, but alas, perfection is a myth. With that in mind, if you cannot catch every issue before a release, at least you can take the proper steps to limit them.
Arjun (my son) sat next to me at my desk. He was a bit nervous but we had practiced 3 times before he was ‘on stage’ in front of hundreds of people and the zoom meeting turned to him. My ten year old began to demonstrate how to deploy an Operational Database in AWS, showcasing how auto-scaling worked and how to set up replication. All of the sales team and my colleagues were quite impressed with him, and I am very proud of him.
When we founded Snowflake, we set out to build an innovative platform. We had the opportunity to take into account what had worked well and what hadn’t in prior architectures and implementations. We saw how we could leverage the cloud to rethink the limits of what was possible.