Business Analytics Data Analytics Forecasting IoT 
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. Now that we have described predictive and prescriptive analytics in detail, what is there left?
Rocket-Powered Data Science
MARCH 19, 2021
How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”
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Smart Data Collective
NOVEMBER 25, 2019
Here are the six trends you should be aware of that will reshape business intelligence in 2020 and throughout the new decade. New Avenues of Data Discovery. New data-collection technologies , like internet of things (IoT) devices, are providing businesses with vast banks of minute-to-minute data unlike anything collected before.
datapine
NOVEMBER 27, 2019
You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on. Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis. How can we make it happen?
Jet Global
MAY 9, 2024
A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.
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