Jet Global
OCTOBER 26, 2021
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.
Jet Global
APRIL 20, 2020
CRM software has gone through a similar transformation, starting with sales force automation, and more recently evolving into a new breed of products that support digital marketing campaigns through email, social media, and online advertising. A new paradigm in reporting and analysis is emerging. Making Sense of Disparate Systems.
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Jet Global
JUNE 5, 2019
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.
Jet Global
APRIL 2, 2019
But business intelligence software , built to give businesses the opportunity to collect, unify, sort, tag, analyze, and report on the vast amounts of data at their disposal, must be a focus for businesses hoping to gain an AI advantage down the road. It All Starts with Data. How should data be tagged, sorted, grouped, and analyzed?
Sisense
AUGUST 11, 2019
BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. Or is Business Intelligence One Part of Business Analytics?
Jet Global
AUGUST 14, 2019
But the vast reams of data generated on a daily basis are presenting a new problem for businesses—what data matters? 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.
Sisense
NOVEMBER 12, 2020
The traditional data warehouses solved the problem of processing and synthesizing large data volumes, but they presented new challenges for the analytics process. Cloud data warehouses took the benefits of the cloud and applied them to data warehouses — bringing massive parallel processing to data teams of all sizes.
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