datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

Cloudera

AUGUST 3, 2021

In summary, predicting future supply chain demands using last year’s data, just doesn’t work. Accurate demand forecasting can’t rely upon last year’s data based upon dated consumer preferences, lifestyle and demand patterns that just don’t exist today – the world has changed.

Analytics 109

Analytics Digital Transformation Risk Forecasting 109

CIO Business Intelligence

MAY 8, 2024

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

Data Integration 52

Data Integration IoT Cost-Benefit Data Quality 52

IBM Big Data Hub

JUNE 14, 2023

In smart factories, IIoT devices are used to enhance machine vision, track inventory levels and analyze data to optimize the mass production process. Artificial intelligence (AI) One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently.

Manufacturing 80

Manufacturing Technology Internet of Things Cost-Benefit 80

Jet Global

MARCH 22, 2023

Market Drivers and Current Trends Organizations are increasing focus on the potential value within big data, seeking to better understand their customers and improve their products. According to Forbes , almost three-quarters of entrepreneurs are already using big data to try and pull ahead of the competition.

Analytics 52

Analytics Cost-Benefit Dashboards Visualization 52

IBM Big Data Hub

DECEMBER 7, 2023

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 64

OLAP Slice and Dice Cost-Benefit Data Warehouse 64

Andrew White

JANUARY 11, 2021

In our modern data and analytics strategy and operating model, a PM methodology plays a key enabling role in delivering solutions. Do you draw a distinction between a data-driven vision and a data-enabled vision, and if so, what is that distinction? where performance and data quality is imperative?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52