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

FineReport

MARCH 24, 2024

They analyze, interpret, and manipulate complex data, track key performance indicators, and present insights to management through reports and visualizations. Data analysts interpret data using statistical techniques, develop databases and data collection systems, and identify process improvement opportunities.

Statistics 52

Statistics Data mining Visualization Reporting 52

datapine

AUGUST 29, 2022

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. 12) Big Data at Work: Dispelling the Myths, Uncovering the Opportunities, by Thomas H.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Grooper

AUGUST 19, 2019

Applied analytics Business analytics Machine learning and data science. Applied Analytics. Applied analytics is all about building a business analytics portfolio of actionable insights which directly affect and improve business processes. Data pipelines. Business Analytics.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

datapine

NOVEMBER 27, 2019

Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 9, 2024

ETL pipelines are commonly used in data warehousing and business intelligence environments, where data from multiple sources needs to be integrated, transformed, and stored for analysis and reporting. This high-quality data is then loaded into a centralized data repository for reporting and analysis.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52