CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 94

Data Lake Unstructured Data Data Warehouse Data Quality 94

CIO Business Intelligence

JANUARY 20, 2023

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. 2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security. 1] [link]. [2]

Analytics 122

Analytics Key Performance Indicator Unstructured Data IoT 122

CIO Business Intelligence

MARCH 22, 2022

To companies entrenched in decades-old business and IT processes, data fiefdoms, and legacy systems, the task may seem insurmountable. Develop a strategy to liberate data . Another option is a data warehouse, which stores processed and refined data. Just starting out with analytics?

Analytics 89

Analytics Key Performance Indicator Data Warehouse Data-driven 89

CIO Business Intelligence

MARCH 9, 2022

Some examples include: Customer 360 analytics, retail inventory and sales analysis, manufacturing operational analysis, eCommerce fraud prevention, network security intelligence, data warehouse consolidation and discount pricing optimization. Just starting out with analytics?

Data-driven 81

Data-driven Analytics Machine Learning Optimization 81

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. Every part of a business generates big Data.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

IBM Big Data Hub

AUGUST 28, 2023

Users have become increasingly hungry for quicker access to trusted and timely data, and a way to access that data with less reliance on the busy Central Analytics Technology team. The Macmillan team realized the need to grow its data culture alongside its revamped BI strategy.

Publishing 50

Publishing Analytics Business Intelligence Operational Reporting 50

datapine

AUGUST 29, 2022

And shows how big data and the advances in analytical technologies are shaping the way the world is perceived. 2) Designing Data-Intensive Applications by Martin Kleppman. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263