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. with a cloud data warehouse is simple.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 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. Network latency : Geographic distances between data and users can introduce latency issues, affecting query performance.

OLAP 62

OLAP Slice and Dice Cost-Benefit Data Warehouse 62

AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. These types of queries are suited for a data warehouse.

Data Warehouse 76

Data Warehouse Data Lake OLAP Cost-Benefit 76

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. It excels in scalability and supports a wide range of analytical use cases.

OLAP 90

OLAP Data Lake Data-driven Snapshot 90