As you may know, analysts typically only have the time to share a small fraction of the information that they have on any topic at any given time, with the majority of our time spent speaking with clients, technologists, and each other.
When Salesforce announced their acquisition of Tableau Monday morning, we at Amalgam Insights obviously started talking to each other about what this meant. Below is a edited excerpt of some of the topics we were going through as I was preparing for PTC LiveWorx in Boston, Data Science analyst Lynne Baer was in Nashville for Alteryx, and DevOps Research Fellow Tom Petrocelli was holding down the fort in Buffalo after several weeks of travel. Hope you enjoy a quick look behind the scenes of how we started informally thinking about this in the first hour or so after the announcement.
When the Salesforce-Tableau topic came up, Tom Petrocelli kicked it off.
On October 17th, I presented a webinar with Incorta’s Chief Evangelist, Matthew Halliday, on the importance of BI architectures in preparing for AI. This webinar is based on a core Amalgam Insights belief that all enterprise analytics and data science activity should be based on a shared core of trusted and consistent data so that Business Intelligence, analytics, machine learning, data science, and deep learning efforts are all based on similar assumptions and can build off each other.
While AI is beginning to impact every aspect of our consumer lives, business data-driven AI seems to be lower on the priority list of most enterprises. The struggle to understand the practical value of AI starts with the lack of ability to make business data easily accessible to the data science teams. Today’s BI tools have not kept up with this need and often are the bottlenecks that stifle innovation.
In this webinar, you will learn from Hyoun Park and Matthew Halliday about:
- key data and analytic trends leading to the need to accelerate analytic access to data.
- guidance for challenges in implementing AI initiatives alongside BI.
- practical and future-facing business use cases that can be supported by accelerating analytic access to large volumes of operational data.
- techniques that accelerate AI initiatives on your business data.
Watch this webinar on-demand by clicking here.