Remove Dashboards Remove OLAP Remove Online Analytical Processing Remove Technology
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Reporting Analytics vs. Financial Reporting: Is There a Difference?

Jet Global

Multi-dimensional analysis is sometimes referred to as “OLAP”, which stands for “online analytical processing.” Technically speaking, OLAP refers to methodologies for producing multidimensional analysis on high-volume data sets.). For excellence in both reporting and analytics, invest in the right tools.

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

Jet Global

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. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age.

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What’s the Difference Between Business Intelligence and Business Analytics?

Sisense

BA and BI are broad terms covering all kinds of technologies and approaches – and, to add to the confusion, are often used interchangeably. So…what is the difference between business intelligence and business analytics? What Does “Business Analytics” Mean? See an example: Explore Dashboard. Is there a difference at all?

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

Jet Global

Finance leaders that were quick to recognize the new paradigm got a head start, using the new technology to make their organizations more efficient and profitable. Over the past few decades, however, technology has been closing that gap. Today’s technology takes this evolution a step further.

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The Future of AI in the Enterprise

Jet Global

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

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

AWS Big Data

Data inbound This section consists of components to process and load the data from multiple sources into data repositories. ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. However, it’s not mandatory to use the same technologies.

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The Future of AI in the Enterprise

Jet Global

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.