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Reporting Analytics vs. Financial Reporting: Is There a Difference?

Jet Global

The terms “reporting” and “analytics” are often used interchangeably. 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. Financial Reporting.

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

Jet Global

A new paradigm in reporting and analysis is emerging. 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).

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Present: After the data has been analyzed and sorted, it is presented to the end user in an understandable format, such as a report, chart or graph. READ BLOG POST.

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

Sisense

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?

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

Jet Global

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

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The Future of AI in the Enterprise

Jet Global

Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.

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

AWS Big Data

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.