Jet Global
OCTOBER 26, 2021
In fact there are some very important differences between the two, and understanding those distinctions can go a long way toward helping your organization make best use of both financial reporting and analytics. Multi-dimensional analysis is sometimes referred to as “OLAP”, which stands for “online analytical processing.”
Jet Global
JUNE 5, 2019
Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Businesses can use data mining to find the information they need and use business intelligence and analytics to determine why it is important. READ BLOG POST.
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Sisense
AUGUST 11, 2019
And, again, the ultimate goals are to better understand how the business is doing, make better-informed decisions that improve performance, and create new strategic opportunities for growth. So, BI deals with historical data leading right up to the present, and what you do with that information is up to you. Confused yet?
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
Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.
Jet Global
AUGUST 14, 2019
The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
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. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.
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