article thumbnail

Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

What is the point of those obvious statistical inferences? In statistical terms, the joint probability of event Y and condition X co-occurring, designated P(X,Y), is essentially the probability P(Y) of event Y occurring. How do predictive and prescriptive analytics fit into this statistical framework? Pay attention!

article thumbnail

What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

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. What is the difference between business analytics and business intelligence? Business analytics techniques.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

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. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics.

article thumbnail

Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

article thumbnail

Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

Comprehensive data processing requires robust data analysis, statistics, and machine learning. In such cases, data analysts run the descriptive analytics to find out, and Python comes into the business. Hence, data preprocessing is essential and required. Python as a Data Processing Technology.

article thumbnail

Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior. The vast majority of financial services companies use the data within their applications for what is called “ Descriptive Analytics.”