Birst BI
OCTOBER 30, 2018
Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior. The vast majority of financial services companies use the data within their applications for what is called “ Descriptive Analytics.”
Rocket-Powered Data Science
OCTOBER 6, 2023
Using the same statistical terminology, the conditional probability P(Y|X) (the probability of Y occurring, given the presence of precondition X) is an expression of predictive analytics. By exploring and analyzing the business data, analysts and data scientists can search for and uncover such predictive relationships.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
datapine
MARCH 25, 2022
On the other hand, BA is concerned with more advanced applications such as predictive analytics and statistic modeling. By using Business Intelligence and Analytics (ABI) tools, companies can extract the full potential out of their analytical efforts and make improved decisions based on facts.
Smart Data Collective
MARCH 11, 2022
Data analytics can assist you in figuring out why people abandon your brand or prefer alternative products instead. Predictive analytics, which analyses historical activities to uncover trends and forecast a specific event, can also predict if a customer is ready to churn or defect. Customer Experience Analytics.
Cloudera
SEPTEMBER 22, 2022
The next step leads to performing exploratory, descriptive analytics, “why is this happening,” and so on. Finally, the end goal is to enable proactive, predictive analytics — “what if” — using applied ML and AI to better predict what will happen and recommend actions to prevent or manage activities as necessary.
IBM Big Data Hub
JULY 27, 2022
The AIOps engine is focused on addressing four key things: Descriptive analytics to show what happened in an environment. Predictive analytics to show what will happen next. Prescriptive analytics to show how to achieve or prevent the prediction. Diagnostics to show why it happened.
Sisense
JUNE 30, 2020
The role of visualizations in analytics. Data visualization can either be static or interactive. Interactive visualizations enable users to drill down into data and extract and examine various views of the same dataset, selecting specific data points that they want to see in a visualized format.
Expert insights. Personalized for you.
73 
Let's personalize your content