Smart Data Collective
JUNE 16, 2022
This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Online analytical processing is a computer method that enables users to retrieve and query data rapidly and carefully in order to study it from a variety of angles.
Jet Global
SEPTEMBER 4, 2020
Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of business objects within the database, such as, customers, general ledger accounts, or purchase orders. Data Lakes.
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Jet Global
APRIL 20, 2020
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). Over the past few decades, however, technology has been closing that gap.
AWS Big Data
MARCH 7, 2023
Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.
Jet Global
JUNE 5, 2019
Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Store and manage: Next, businesses store and manage the data in a multidimensional database system, such as OLAP or tabular cubes. Start future proofing your business today.
Jet Global
AUGUST 14, 2019
Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.
Jet Global
OCTOBER 2, 2019
Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.
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