Ontotext

JUNE 10, 2021

Relational databases benefit from decades of tweaks and optimizations to deliver performance. To handle such scenarios you need a transalytical graph database – a database engine that can deal with both frequent updates (OLTP workload) as well as with graph analytics (OLAP). It provides meaning.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Sisense

SEPTEMBER 3, 2019

OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). An OLAP database is best for situations where you read from the database more often than you write to it. OLAP databases excel at queries that require large table scans (e.g.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Jet Global

MAY 1, 2023

These benefits provide a 360-degree feedback loop. In this new era, users expect to reap the benefits of analytics in every application that they touch. Users are coming to expect sophisticated analytics at little or no cost. All benefit from the enhanced functionality and additional reporting and analytics.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52