Sisense

OCTOBER 6, 2020

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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

Grooper

AUGUST 19, 2019

Traditional data sources like end of month statements and quarterly reports are no longer enough. Access to enterprise-wide information fuels analytics solutions and enable a new approach for decision making. It includes the reports, charts, dashboards, and terminology unique to your organization. Master data management.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

CIO Business Intelligence

APRIL 4, 2023

AI working on top of a data lakehouse, can help to quickly correlate passenger and security data, enabling real-time threat analysis and advanced threat detection. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. Want to learn more?

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52