Data Collection OLAP Visualization 
CIO Business Intelligence
JANUARY 20, 2023
But the benefits of BI extend beyond business decision-making, according to data visualization vendor Tableau , including the following: Data-driven business decisions: The ability to drive business decisions with data is the central benefit of BI.
FineReport
JUNE 24, 2021
Originally, Excel has always been the “solution” for various reporting and data needs. However, along with the diffusion of digital technology, the amount of data is getting larger and larger, and data collection and cleaning work have become more and more time-consuming. Data visualization analysis.
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FineReport
AUGUST 14, 2020
The underlying data is in charge of data management, covering data collection, ETL, building a data warehouse, etc. The data analysis part is responsible for extracting data from the data warehouse, using the query, OLAP, data mining to analyze data, and forming the data conclusion with data visualization.
Smart Data Collective
OCTOBER 25, 2023
Well, it is – to the ones that are 100% familiar with it – and it involves the use of various data sources, including internal data from company databases, as well as external data, to generate insights, identify trends, and support strategic planning. In the 1990s, OLAP tools allowed multidimensional data analysis.
FineReport
FEBRUARY 28, 2020
Enterprise reporting is a process of extracting, processing, organizing, analyzing, and displaying data in the companies. It uses enterprise reporting tools to organize data into charts, tables, widgets, or other visualizations. The central one is the data visualization technology at the display level.
Jet Global
AUGUST 14, 2019
And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. This also helps business functions avoid unnecessary data logjams and giving them instant access they need to the data they so desperately require.
Smart Data Collective
APRIL 2, 2019
The primary reason data lakes were so attractive to companies was the promise of agile processing of data in order to provide real-time (or near real-time) results on data sets. In order for this to even be possible, the data visualization aspect needs to be streamlined to show exactly what the user wants to see.
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