FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. I purchased a data analytics system, but my company did not use it ?

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Jet Global

NOVEMBER 5, 2020

For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements. Azure Data Lakes are complicated.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

OCTOBER 18, 2023

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.

Analytics 95

Analytics Data Warehouse Testing Dashboards 95

Jet Global

OCTOBER 22, 2020

Most organizations are looking for sophisticated reporting and analytics, but they have little appetite for managing the highly complicated infrastructure that goes with it. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 52

Jet Global

MAY 1, 2023

Application Imperative: How Next-Gen Embedded Analytics Power Data-Driven Action Download Now While traditional BI has its place, the fact that BI and business process applications have entirely separate interfaces is a big issue. Why Are Embedded Analytics a 100% Must-Have? Financial Services represent 13.0

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52