Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. TDWI – David Loshin.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

Ontotext

APRIL 15, 2020

Knowledge graphs are collections of live, richly interconnected, machine-processable knowledge that use formal semantics and automated reasoning to enable deep analytics. Their ability to derive new knowledge out of existing facts and uncover hidden relationships make them best suited to analyze rapidly changing data from disparate sources.

Publishing 105

Publishing Metadata Data mining Technology 105

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. DataOps Project Design and Implementation.

Testing 152

Testing Metadata Dashboards Statistics 152

CIO Business Intelligence

JULY 28, 2023

This strategic initiative also makes data consistently available for insight and maintains its integrity. Without a coherent strategy, enterprises face heightened security risks, rocketing storage costs, and poor-quality data mining. Many enterprises have become data hoarders, however.

Risk 83

Risk Management Cost-Benefit Data mining 83

FineReport

MARCH 31, 2024

Acting as a comprehensive solution, the best BI tools collect and analyze company data to generate easily interpretable graphs, reports, and charts , leveraging advanced data mining, analytics, and visualization techniques. Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52