Analytics

Adobe brings AI-powered Virtual Analyst to Analytics Cloud

Adobe will today announce the introduction of Virtual Analyst, powered by its Sensei AI.

The analyst runs 24/7 in the background to monitor data and detect and find the root cause of anomalies in online activity. This replaces the painstaking process of an engineer or data team manually searching analytics reports for insights, which can diminish in value over time.

“Insights we do believe have a shelf life and to have a system be automated and can handle these on its own is really key, I think,” Adobe marketing manager Nate Smith told VentureBeat in a phone interview.

Sensei was first introduced last fall as an artificial intelligence service trained by massive amounts of data gathered from Adobe Creative, Marketing, and Analytics cloud software.

Sensei can do things like auto-caption images, deliver data insights, or talk people through how to use Adobe software. Adobe ultimately wants the AI to also train novice creatives how to…

Dataiku Offers Advice on how to Create Data Team Harmony

Harmony and analytics are two terms not often found together, especially when executing data science chores using a team of diverse data professionals. A data science team is often made up of people from diverse backgrounds, with diverse skillsets – from the machine learning specialist to the master Python coder, to the beginning data analyst. To successfully build and execute any sized data science project requires harmony across all of the team members. Everyone needs to work effectively and efficiently, using the tools they know best.

GigaOM recently had the opportunity to discuss the dynamics of building data teams with Florian Douetteau, CEO of Dataiku. Douetteau offered some sage advice and was able to point out what challenges face those trying to build teams.

Douetteau said “one of the biggest challenges is finding, hiring, and keeping people with a background in machine learning. There is a high demand for experienced data scientists, meaning that it can cost a lot to hire one, especially considering the opportunities data scientist have.”

Douetteau added “yet so many of those data professionals are specialized in their area of expertise, meaning that it is difficult for a business to maximize the return on investment of hiring a data scientists. In other words, to build a team, businesses need to move beyond a single individual’s domain of expertise and hire individuals with different skill sets and enable them to work cooperatively and productively.”

The growing deficit of Data Scientists, along with the closed nature of many analytics tools have made building effective teams a near impossibility. Yet all is not lost. Douetteau said, “there exists a vast ecosystem of opensource tools that are available to the masses, which can help to level the playing field, and bring data analytics capabilities to professionals of all stripes.”

However, much like the cola wars of the 80’s, there is an almost infinite variety of flavors and formulas that drive tastes, at least when it…