Remove data-science-roadmap
article thumbnail

How to build a successful AI strategy

IBM Big Data Hub

Whether it’s deeper data analysis, optimization of business processes or improved customer experiences , having a well-defined purpose and plan will ensure that the adoption of AI aligns with the broader business goals. A successful AI strategy should act as a roadmap for this plan.

article thumbnail

Machine Learning Product Management: Lessons Learned

Domino Data Lab

This Domino Data Science Field Note covers Pete Skomoroch ’s recent Strata London talk. Over the years, I have listened to data scientists and machine learning (ML) researchers relay various pain points and challenges that impede their work. It focuses on his ML product management insights and lessons learned.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Plant Seeds for Future Growth: What to Expect at TIBCO Analytics Forum 2021

TIBCO

This year, embrace the spirit of spring at the TIBCO Analytics Forum (TAF) 2021 by learning about new analytics and data management technologies and approaches and how to foster growth in the coming years. And get a head start on upping your analytics knowledge by exploring the TIBCO Community Blog and Spotfire demo gallery.

article thumbnail

DataRobot and SAP Partner to Deliver Custom AI Solutions for the Enterprise

DataRobot Blog

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

article thumbnail

Sisense AI – What it Really Takes to Build a Better Mousetrap

Sisense

This effort is beginning to bear significant fruit with the introduction of AI Exploration Paths as well as an aggressive roadmap for this year and beyond. Augmented Insights is how we refer to the area of our AI research that is dedicated to providing business users with a guided journey and deeper insights from their data.

IT 74
article thumbnail

The year’s top 10 enterprise AI trends — so far

CIO Business Intelligence

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Traditional ML requires a lot of data, experienced data scientists, as well as training and tuning. It’s incredible,” he says.

article thumbnail

Predictive Analytics in Manufacturing: A Winning Edge

Sisense

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. It requires a skilled data team, advanced tools, and enormous amounts of clean data from the right combination of inputs. The process of producing goods is an enormous opportunity for data optimization.