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 73

Data Integration IoT Cost-Benefit Data Quality 73

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 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 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

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