Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions using Vertex AI.

MiHCM combines Machine Learning techniques to deliver Smart Analytics on Workforce & Talent Data by connecting and sourcing data from historic data points and surfacing insights as coherent stories.

Organisations are looking for technologies that help more people do sophisticated analysis. At Tableau, we're investing in analytical capabilities that help anyone – from data scientists to business users – get to answers faster and uncover unanticipated insights. Through machine learning, statistics, natural language and smart data prep, we are making analytics more approachable to users of all skill levels.

Infor Coleman is a powerful artificial intelligence platform designed specifically for business users – built upon a foundation of industry-specific data. At any given moment, it can help with executing tasks, recommending next-best sales offers, and even predicting maintenance issues and adjusting production schedules accordingly. The platform is named after the inspiring physicist and mathematician Katherine Coleman Johnson, whose trail-blazing work helped U.S. astronauts land on the moon, Coleman represents a giant leap for artificial intelligence at scale.

I've spent most of my career in Business Intelligence, either as part of a technology organization developing BI tools or as an analyst using BI and analytics to make decisions. I've always been passionate about using cutting edge technology to solve business pain points, so I was very excited to join Birst to lead the development of Smart Analytics. Driven by Machine Learning, we aim to make Birst Smart Analytics usable by any business person to generate insights needed to understand what is impacting their business, without the assistance of an analyst or IT.

I've spent most of my career in Business Intelligence, either as part of a technology organization developing BI tools or as an analyst using BI and analytics to make decisions. I've always been passionate about using cutting edge technology to solve business pain points, so I was very excited to join Birst to lead the development of Smart Analytics. Driven by Machine Learning, we aim to make Birst Smart Analytics usable by any business person to generate insights needed to understand what is impacting their business, without the assistance of an analyst or IT.

Constellation Research is a Silicon Valley-based technology research and advisory firm specializing in digital transformation and disruptive technologies. In this recent report, author Doug Henschen, VP and Principal Analyst, explores the evolution of self-service BI and the rise of smart analytics in the market, examining four key areas in which Tableau continues to invest: Data prep, data analysis and discovery, natural language interactions, and predictive analytics. With a greater variety of data and increased demand to use it, Tableau is not just out to democratize data, but to make complex analyses of it simpler--speeding up insight to action. Technologies like machine learning, natural language processing, and smart algorithms (all under the umbrella of smart analytics), are a great opportunity for the world of analytics to take the next big leap. Tableau is at the forefront of this new era pushing the boundaries of what's possible to help more people than ever before see and understand data.

Machine learning and artificial intelligence advances in five areas will ease data prep, discovery, analysis, prediction and data-driven decision making. For ten years the prevailing trend in business intelligence (BI) and analytics has been the move toward self service. In 2018 and beyond we'll see a growing list of what many call "smart" capabilities powered by machine learning (ML) and artificial intelligence (AI). These features are sure to help us move beyond the limits of the self-service era. As I explain in a my latest report, "How Machine Learning & Artificial Intelligence Will Change BI & Analytics," we're already starting to see smart capabilities in five areas: data prep, discovery, analysis, prediction and AI-powered, prescriptive applications.