article thumbnail

Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

article thumbnail

How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Cloud based solutions are the future of the data warehousing market.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Digital Transformation is a Data Journey From Edge to Insight

Cloudera

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

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

Data Mining vs Data Warehousing: 8 Critical Differences

Analytics Vidhya

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

article thumbnail

How the Edge Is Changing Data-First Modernization

CIO Business Intelligence

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. How edge refines data strategy.

IoT 81