Jet Global

OCTOBER 26, 2021

Multi-dimensional analysis is sometimes referred to as “OLAP”, which stands for “online analytical processing.” Visualizations : Data visualizations, including charts, graphs, maps, and similar graphical components, provide an especially powerful tool for quickly identifying patterns within large data sets.

Reporting 98

Reporting Slice and Dice OLAP Analytics 98

Octopai

JANUARY 21, 2020

However, over time new technologies and tools developed to ease data reporting and analysis. This is how the Online Analytical Processing (OLAP) cube was born, which you might call one of the grooviest BI inventions developed in the 70s. Saving time and headaches with online analytical processing tool.

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

Jet Global

AUGUST 14, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Sisense

AUGUST 11, 2019

BA and BI are broad terms covering all kinds of technologies and approaches – and, to add to the confusion, are often used interchangeably. So…what is the difference between business intelligence and business analytics? What Does “Business Analytics” Mean? Is there a difference at all? Let’s take a closer look.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Jet Global

SEPTEMBER 4, 2020

Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Jet Global

OCTOBER 2, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

AWS Big Data

MARCH 7, 2023

Data inbound This section consists of components to process and load the data from multiple sources into data repositories. ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. However, it’s not mandatory to use the same technologies.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68