Jet Global
APRIL 2, 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. When many of today’s business leaders are looking to implement AI, what they really mean is they want more actionable insight into their data.
CIO Business Intelligence
JANUARY 20, 2023
BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.
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FineReport
AUGUST 14, 2020
It is composed of three functional parts: the underlying data, data analysis, and data presentation. The underlying data is in charge of data management, covering data collection, ETL, building a data warehouse, etc.
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.
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. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
Smart Data Collective
APRIL 2, 2019
Because of the types of databases that made their way into adoption during the nascent days of Big Data, we now have the problem of streamlining databases running on Hive or NoSQL that were never meant to process data sets as large as what our data lake holds. The Third Problem – Preparation of Data.
FineReport
FEBRUARY 28, 2020
According to the process from data to knowledge, the functional architecture of a general enterprise reporting system is shown below:It is divided into three functional levels: the underlying data, data analysis, and data presentation.
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