erwin

JUNE 7, 2022

Machine Learning. I published my first book in 2003 showcasing how I used Ralph’s technique to create a large data warehouse in the Oracle database. The first and most important thing to recognize and understand is the new and radically different target environment that you are now designing a data model for. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Also, datasets are accessed for ML, data exporting, and publishing needs. Data outbound Data is often consumed using structured queries for analytical needs.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

FineReport

MAY 13, 2020

And, with Tableau Public, published workbooks are “disconnected” from the underlying data sources and require periodic updates when the data changes. It provides data scientists and BI executives with data mining, machine learning, and data visualization capabilities to build effective data pipelines. . From Google.

OLAP 105

OLAP KPI Data mining Business Intelligence 105

Jet Global

MAY 1, 2023

OLAP cubes Used for multi-dimensional analysis Strategic Objective When a vendor-specific connector is not available, generic connectors provide flexibility with data. Augmented analytics use machine learning and AI to aid with data insight and analysis to improve workers’ ability to analyze data. Instead, software can be used.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52