Data Science Descriptive Analytics Machine Learning Predictive Modeling 
IBM Big Data Hub
SEPTEMBER 19, 2023
Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.
CIO Business Intelligence
JUNE 7, 2022
To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? Data analytics methods and techniques.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Domino Data Lab
JANUARY 21, 2021
Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. imputation of missing values). ref: [link].
Rocket-Powered Data Science
OCTOBER 6, 2023
In the enterprise, sentinel analytics is most timely and beneficial when applied to real-time, dynamic data streams and time-critical decisions. The analytics triage is critical, to avoid alarm fatigue (sending too many unimportant alerts) and to avoid underreporting of important actionable events. Pay attention!
datapine
JANUARY 31, 2022
BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.
Expert insights. Personalized for you.
84 
Let's personalize your content