Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. Teams at Facebook developed Presto to handle high numbers of concurrent queries on petabytes of data and designed it to scale up to exabytes of data.

OLAP 88

OLAP Data Lake Data-driven Snapshot 88

AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. To house our data, we need to define a data model.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

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. This siloed approach often resulted in data redundancy and complexity, hampering integration with other business systems.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. These campaigns are optimized by using an AI-based bid process that requires running hundreds of analytical queries per campaign.

Big Data 68

Big Data Data Warehouse Advertising OLAP 68

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73