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 130

Online Analytical Processing OLAP Analytics Data Warehouse 130

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 219

OLAP Online Analytical Processing Data Science Publishing 219

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 228

OLAP Online Analytical Processing Data Science Publishing 228

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. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

OLAP 60

OLAP Slice and Dice Cost-Benefit Data Warehouse 60

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 90

OLAP Data Lake Data-driven Snapshot 90

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 143

Business Intelligence Dashboards Data mining OLAP 143

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