Jet Global

SEPTEMBER 4, 2020

The Data Warehouse Approach. 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. There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”).

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. We explore why Aura chose this solution and what technological challenges it helped solve.

Big Data 66

Big Data Data Warehouse Advertising OLAP 66

Sisense

NOVEMBER 12, 2020

While the architecture of traditional data warehouses and cloud data warehouses does differ, the ways in which data professionals interact with them (via SQL or SQL-like languages) is roughly the same. The primary differentiator is the data workload they serve. Traditional data warehouses. Cloud data warehouses.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Jet Global

OCTOBER 22, 2020

The world of business analytics is evolving rapidly. As ERP moves to the cloud, software vendors are developing more sophisticated, interconnected ways of gathering, organizing, and analyzing business data. 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

IBM Big Data Hub

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 64

OLAP Slice and Dice Cost-Benefit Data Warehouse 64

IBM Big Data Hub

SEPTEMBER 25, 2023

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. Consider the magnitude of Uber’s footprint.

OLAP 95

OLAP Data Lake Data-driven Snapshot 95