Smart Data Collective

JUNE 16, 2022

Data science is both a rewarding and challenging profession. One study found that 44% of companies that hire data scientists say the departments are seriously understaffed. Fortunately, data scientists can make due with fewer staff if they use their resources more efficiently, which involves leveraging the right tools.

Online Analytical Processing 139

Online Analytical Processing OLAP Analytics Data Warehouse 139

CIO Business Intelligence

JANUARY 20, 2023

The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs. That company could also use its BI capabilities to discover which products are most commonly delayed or which modes of transportation are most often involved in delays.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

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. It organizes data into user-friendly structures, aligning with shared business definitions, ensuring users can analyze data with ease despite changes.

OLAP 109

OLAP Analytics Visualization Dashboards 109

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 97

Analytics Data Warehouse Data Lake Metadata 97

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 86

OLAP Data Lake Data-driven Online Analytical Processing 86

Jet Global

AUGUST 14, 2019

Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Sisense

SEPTEMBER 3, 2019

First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). Think of it like something that houses the metrics used to power daily, weekly, or monthly business KPIs. roll-ups of many rows of data). OLTP vs OLAP.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78