AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Thanks to a real-time BI dashboard, you suddenly notice a spate of orders that are coming in with a gross margin of less than 5%.

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Online Analytical Processing (OLAP).

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

Jet Global

OCTOBER 22, 2020

Power BI provides users with some very nice dashboarding and reporting capabilities. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. This leads to the second option, which is a data warehouse. The first is an OLAP model. Fast-forward to 2020.

Modeling 52

Modeling OLAP Reporting Sales 52

AWS Big Data

MARCH 20, 2023

The data from the Kinesis data stream is consumed by two applications: A Spark streaming application on Amazon EMR is used to write data from the Kinesis data stream to a data lake hosted on Amazon Simple Storage Service (Amazon S3) in a partitioned way.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87