AWS Big Data

MARCH 7, 2023

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. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

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. So how is the data extracted?

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

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. So how is the data extracted?

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

Sisense

SEPTEMBER 3, 2019

Fundamentally they are different than transactional databases we’ve seen in the past, and before we jump into how to build your data warehouse, it’s important to understand that distinction. OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber chose Presto for the flexibility it provides with compute separated from data storage. As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87

Jet Global

MAY 28, 2019

But the foundational step in getting the data to drive your business forward is first ensuring it can be collected and identified in a way that makes it simple to find and report on with the insights that matter. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise? Download Now.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85