CIO Business Intelligence
JULY 5, 2022
What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. The discipline is a key facet of the business analyst role. Business analytics techniques.
IBM Big Data Hub
OCTOBER 5, 2022
With the right technology-foundation in place, it becomes easier to tackle the business alignment questions, starting with designing an end-to-end integrated business planning process that will lead efficiently to a consensus forecast (or plan).
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IBM Big Data Hub
SEPTEMBER 19, 2023
An electrical engineer can use prescriptive analytics to digitally design and test out various electrical systems to see expected energy output and predict the eventual lifespan of the system’s components. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred.
Smart Data Collective
AUGUST 7, 2019
With the right log management tool, IT admins can easily access ready-made dashboards and generate reports which visualize essential events that lead to pre-emptive actions and sound decisions. Some of the practical applications of CRM analytics include: Creating customer groups. Creating predictive models.
Smarten
JUNE 29, 2018
The Paired Sample T Test used to determine whether the mean of a dependent variable and is particularly useful in measuring results before and after a particular event, action, process change, etc. Paired Sample T testing can be applied only to two samples: one measure and one time dimension. About Smarten.
Cloudera
NOVEMBER 2, 2020
Ingest 100s of TB of network event data per day . The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. 200,000 queries per day.
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?
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