Jet Global

APRIL 2, 2019

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions. So how is the data extracted?

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

AWS Big Data

AUGUST 6, 2024

Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. Internal dashboards – Providing analytics that are relevant to stakeholders across the organization for internal use.

OLAP 93

OLAP Analytics Visualization Dashboards 93

Jet Global

AUGUST 14, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

IBM Big Data Hub

SEPTEMBER 25, 2023

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them!

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

AUGUST 1, 2024

This includes the expected response time limits for dashboard queries or analytical queries, elapsed runtime for daily ETL jobs, desired elapsed time for data sharing with consumers, total number of tenants with concurrency of loads and reports, and mission-critical reports for executives or factory operations.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

AWS Big Data

MARCH 7, 2023

Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

Jet Global

OCTOBER 2, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Sisense

SEPTEMBER 3, 2019

First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). For example, if you are using Redshift solely for analytics purposes, you can scale the cluster up with more nodes when this happens and resume work once it is complete.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78