DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices.

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description. Semi-structured data falls between the two.

Unstructured Data 134

Unstructured Data Data Analytics Analytics Structured Data 134

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

DataRobot

APRIL 19, 2021

But for more complex business decisions, including those that use less structured data, we have artificial intelligence systems. Most modern artificial intelligence systems are powered by machine learning algorithms , which learn by example.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

Corinium

APRIL 25, 2019

The areas of fastest AI innovation and adoption are around machine learning, using it for more and more use cases where there exists large volumes of data, and human beings just don’t have the bandwidth or can’t keep up with ongoing stream of transactions, events, or whatever other changes in the environment being described by that data.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

NOVEMBER 25, 2020

A discovery data warehouse is a modern data warehouse that easily allows for augmentation of existing reports and structured data with new unstructured data types, and that can flexibly scale with volume and compute needs. Matthew’s company is not alone in this situation.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

CIO Business Intelligence

MARCH 6, 2023

We use Snowflake very heavily as our primary data querying engine to cross all of our distributed boundaries because we pull in from structured and non-structured data stores and flat objects that have no structure,” Frazer says. “We think we found a good balance there.

Data Lake 62

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 62