CIO Business Intelligence

MARCH 22, 2022

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? The data governance, however, is still pretty much over on the data warehouse.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”). On-premises business intelligence and databases. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

JULY 2, 2019

Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

O'Reilly on Data

SEPTEMBER 11, 2019

Deep learning,” for example, fell year over year to No. Increasingly, the term “data engineering” is synonymous with the practice of creating data pipelines, usually by hand. In quite another respect, however, modern data engineering has evolved to support a range of scenarios that simply were not imaginable 40 years ago.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

CDW Research Hub

SEPTEMBER 15, 2020

Creating a modern data platform that is designed to support your current and future needs is critical in a data-driven organization. Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Easy Access with a Secure Foundation. Need one-on-one support?

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

CIO Business Intelligence

JANUARY 20, 2023

And to give employees access to the data they need, organizations will need to move away from legacy systems that are siloed, rigid and costly to new solutions that enable analytics and AI with speed, scalability, and confidence. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137