Remove Analytics Remove Business Intelligence Remove Data Warehouse Remove OLAP
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Financial Intelligence vs. Business Intelligence: What’s the Difference?

Jet Global

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Whereas business intelligence is tactical, financial intelligence is strategic. .

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. READ BLOG POST.

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Why Business Intelligence is Top of Mind for CFOs for 2022

Jet Global

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. Discover Meaning Amid All That Data. Why business intelligence ?

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

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The Business Intelligence Market – What’s Old is New

In(tegrate) the Clouds

As the data visualization, big data, Hadoop, Spark and self-service hype gives way to IoT, AI and Machine Learning, I dug up an old parody post on the business intelligence market circa 2007-2009 when cloud analytics was just a disruptive idea. Thanks to The OLAP Report for lots of great market materials.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

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The Enterprise AI Revolution Starts with BI

Jet Global

In a recent McKinsey survey of 3,000 business executives, 41% responded that they were uncertain of the benefits of AI for their business. Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. It All Starts with Data.