Rocket-Powered Data Science
MARCH 19, 2021
This article quotes an older market projection (from 2019) , which estimated “the global industrial IoT market could reach $14.2 Another dimension to this story, of course, is the Future of Work discussion, including creation of new job titles and roles, and the demise of older job titles and roles. trillion by 2030.”.
Smarten
MAY 31, 2022
The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Descriptive Statistics. Competitive Changes. Market Changes. Trends and Patterns. Trends and Patterns. Forecasting.
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FineReport
MARCH 24, 2024
This article explores the data analyst job description, covering essential skills, tools, education, certifications, and experience. Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios.
Smarten
FEBRUARY 16, 2023
Gartner says that a Citizen Data Scientist is “a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.” In this article, we consider the question of ‘what’s in it for me?’
IBM Big Data Hub
JULY 6, 2023
Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.
FineReport
JULY 28, 2021
If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. Photo by Chris Ried on Unsplash. What is Business Intelligence?
Rocket-Powered Data Science
MARCH 10, 2020
Ahh, that’s the topic for another article. Chapter 1 provides a beautiful introduction to graphs, graph analytics algorithms, network science, and graph analytics use cases. Incorporating context into the graph (as nodes and as edges) can thus yield impressive predictive analytics and prescriptive analytics capabilities.
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