Einstein Discovery is AI-powered analytics that enables business users to automatically discover relevant patterns based on their data – without having to build sophisticated data models. However, Einstein Discovery is only as good as the historical data it is analyzing. Wrangling the data, which is always the hardest part, involves cleaning and consolidating your historical ...
So far in this series we have introduced the notion of Einstein Analytics Stories, why you may create one and from a high level what sorts of business problems and analyses you can approach using a Story. But, we’re sure you are aware, Stories are just part of the business problem you are tackling – ...
Before getting started with creating first your Einstein Analytics Plus Stories, there are some things you need to think through and decide. Typically people are concerned about data, but we will save that for later. But even before rolling up your sleeves and finding and crunching data, the most important pre-creation task is the need ...
When I started working with Einstein Analytics in 2015 needless to say not many knew much about Einstein Analytics. In the past couple of years, the DataTribe as we call it has emerged and we have grown in numbers. I find many more being knowledgeable on Einstein Analytics in terms of visualization and data prep, ...
🇯🇵 Read in Japanese Einstein Discovery accelerates the embedding of augmented analytics in a business user’s work environment. The predictive models are created by the platform using a “No Code AI Approach”, which means that the algorithms to train these models are part of the solution, and don’t need to be coded by advanced developers ...
🇯🇵 Read in Japanese As artificial intelligence, and specifically machine learning, is conquering today’s business world, a new way of human machine interaction enters our professional lives. We are more and more guided by predictive models that prioritise our work and give recommendations to improve our business. Once widely adopted, this embedding of so-called augmented ...
