A.I. (Artificial Intelligence) is increasingly entering the mainstream. Like the invention of the steam engine new electricity, A.I. will transform every aspect of our lives, including enterprise applications. This demo will give you a quick look at the Infor Coleman digital assistant’s basic capabilities.
In the previous post, we discovered the first five most common Business Intelligence terms you need to know. In today's post, we will go through the next six.
If you are new to Business Intelligence (BI), navigating through its terminology is not an easy thing to do, which is why we are here to help.
In the previous post, we discovered why data analytics is important to Tesla and applications of Tableau software at this electric car maker. In this post, we will further examine other applications.
Grab, the leading car-sharing service in Southeast Asia, has adopted a Tableau BI solution to make more informed, data-driven decisions across their entire organisation. The ability to analyse millions of rows of data at lightning speed has allowed Grab product teams to track multiple metrics in real-time and better understand customer preferences in different regions.
Both enterprises and individuals have to process some kind of data every day, whether it is a short message, a notification, a piece of news, statistics, a video, etc. If we accumulate all the data acquired in a month, the amount guarantees to shock anyone.
Today, Business Intelligence or Business Analytics sounds like a novel concept born in the Digital Age. But the first Business Intelligence-like application was actually created more than 65 years ago in a British tea shop.
Everybody seems to talk about blockchain these days. But what exactly is blockchain? There is no shortage of definitions on the internet, but many are too technical for a typical C-level executive to understand.
Managing enterprise data may seem like a daunting task. It can easily get overwhelming and out of control if not managed well. In a survey conducted by Primary Data in 2016, the results showed that a common trait among many enterprise IT experts that they have to handle 10 to 20, sometimes more, data sources as the company grows. How can you simplify your data management? Check out this infographic for the answer.