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.
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. Predictive analytics and modeling.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Jet Global
APRIL 2, 2019
Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. 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.
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. Analytics and reporting: Capturing, structuring, and storing data is good—but being able to analyze and report on it is the ultimate end goal.
FineReport
APRIL 20, 2020
Compared to reporting tools, they can realize data forecast thanks to OLAP analysis and data mining technologies. Besides, in many cases, the data is not entirely grouped, but in the form of fixed columns or segments. All data is divided into strip-shaped models in Crystal Report. Reporting fragment .
Jet Global
OCTOBER 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. Analytics and reporting: Capturing, structuring, and storing data is good—but being able to analyze and report on it is the ultimate end goal.
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.
Expert insights. Personalized for you.
143 
Let's personalize your content