Remove OLAP Remove Online Analytical Processing Remove Reporting Remove Risk
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BI Cubed: Data Lineage on OLAP Anyone?

Octopai

How much time has your BI team wasted on finding data and creating metadata management reports? However, over time new technologies and tools developed to ease data reporting and analysis. This is how the Online Analytical Processing (OLAP) cube was born, which you might call one of the grooviest BI inventions developed in the 70s.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

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. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

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How to Build a Performant Data Warehouse in Redshift

Sisense

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. Redshift is a type of OLAP database.

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Financial Intelligence vs. Business Intelligence: What’s the Difference?

Jet Global

A new paradigm in reporting and analysis is emerging. There was always a delay between the events being recorded in financial systems (for example, the purchase of a product or service) and the ability to put that information in context and draw useful conclusions from it (for example, a weekly sales report).

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Data Model Development Using Jinja

Sisense

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Jinja provides a powerful automatic HTML escaping feature. Sandboxing.