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

Analytics Vidhya

JULY 1, 2022

This article was published as a part of the Data Science Blogathon. Introduction In the field of Data Science main types of online processing systems are Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP), which are used in most companies for transaction-oriented applications and analytical work.

OLAP 270

OLAP Online Analytical Processing Data Science Publishing 270

Analytics Vidhya

SEPTEMBER 15, 2022

This article was published as a part of the Data Science Blogathon. Introduction DuckDB is designed to support analytical query workloads, also known as Online analytical processing (OLAP).” In short, […].

OLAP 271

OLAP Online Analytical Processing Data Science Publishing 271

CIO Business Intelligence

JANUARY 20, 2023

While the predictions and advice derived from business analytics requires data science professionals to analyze and interpret, one of the goals of BI is that it should be easy for relatively non-technical end users to understand, and even to dive into the data and create new reports.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

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

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 93

OLAP Analytics Visualization Dashboards 93

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 78

Analytics Data Warehouse Data Lake Metadata 78