Rocket-Powered Data Science
OCTOBER 6, 2023
Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?
IBM Big Data Hub
NOVEMBER 20, 2019
In this blog post, we’ll share real-world stories of how decision optimization technology delivers prescriptive analytics capabilities and opens the door to operational efficiency. We will also introduce you to the IBM data science and AI platform solutions that can deliver operational efficiency that satisfies the business.
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FineReport
JULY 28, 2021
Good data can give you keen insights, convincing evidence to make informed decisions. By observing and analyzing data, we can develop more accurate theories and formulate more effective solutions. For this reason, data science and/vs. Definition: BI vs Data Science vs Data Analytics.
IBM Big Data Hub
JULY 6, 2023
While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.
CIO Business Intelligence
NOVEMBER 14, 2022
With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. Optimization analysis models. Analytics, Data Science Model-driven DSS.
FineReport
MARCH 24, 2024
Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis.
AWS Big Data
MARCH 26, 2024
Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.
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