Rocket-Powered Data Science

JULY 14, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 166

Analytics Internet of Things Prescriptive Analytics Data Science 166

Rocket-Powered Data Science

JULY 7, 2019

is also sometimes referred to as IIoT (Industrial Internet of Things) or Smart Manufacturing, because it joins physical production and operations with smart digital technology, Machine Learning, and Big Data to create a more holistic and better connected ecosystem for companies that focus on manufacturing and supply chain management.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

JANUARY 24, 2024

With nearly 800 locations, RaceTrac handles a substantial volume of data, encompassing 260 million transactions annually, alongside data feeds from store cameras and internet of things (IoT) devices embedded in fuel pumps.

Data Strategy 135

Data Strategy Strategy Unstructured Data Data Governance 135

IBM Big Data Hub

NOVEMBER 3, 2023

Unlike magnetic storage (such as HDDs and floppy drives) that store data using magnets, solid-state storage drives use NAND chips, a non-volatile storage technology that doesn’t require a power source to maintain its data. What is NVMe?

Cost-Benefit 73

Cost-Benefit Enterprise Internet of Things Technology 73

BizAcuity

MARCH 1, 2019

There is a coherent overlap between the Internet of Things and Artificial Intelligence. IoT is basically an exchange of data or information in a connected or interconnected environment. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Future of IoT is AI.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Sisense

MAY 11, 2021

Maybe one of the most common applications of a data model is for internal analysis and reporting through a BI tool. In these cases, we typically see raw data restructured into facts and dimensions that follow Kimball Modeling practices. building connections via business logic between two data sources) Merging (e.g.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

MARCH 7, 2023

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74