This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
To better understand multiple linear regression, let’s look at one such analysis of independent variables: Temperature and Humidity, and a target variable (yield). How Can Multiple Linear Regression Be Helpful for BusinessAnalysis? Use Case – 1.
How is Spearman’s Rank Correlation Useful for BusinessAnalysis? Business Problem: An educational organization wants to assess students’ rating, based on two different sources of observation. The closer this value is to 0, the weaker the relationship/association is between both variables. Use Case – 1.
How is the Paired Sample T Test Beneficial to BusinessAnalysis? This type of analysis can be useful in numerous situations. Let’s look at two use cases to better understand the benefit of this technique in businessanalysis. Therefore, the treatment was not effective. Use Case – 1.
How Does Frequent Pattern Mining Support BusinessAnalysis? This method of analysis can be useful in evaluating data for various business functions and industries. Basket Data Analysis – To analyze the association of purchased items in a single basket or single purchase. Confidence (milk->bread) = 0.5
Assisted predictivemodeling suggests techniques to analyze data that will result in the right outcome for the goals of the analysis. Self-serve data preparation walks the user through the data preparation process so that they can easily prepare data for analysis without the assistance of IT or a data scientist.
How Can Outlier Detection Improve BusinessAnalysis? The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.
This article looks at the ARIMAX Forecasting method of analysis and how it can be used for businessanalysis. An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or more moving average (MA) terms.
How Can the Chi Square Test of Association Be Used for BusinessAnalysis? Business Problem: A retail store marketing manager wants to know if there is a significant association between the geography of a customer and his/her brand preferences. Use Case – 1.
Use Case(s): Weather Forecasting, Fraud Analysis and more. Frequent Pattern Mining (Association): What is Frequent Pattern Mining (Association) and How Does it Support BusinessAnalysis? Use Case(s): Market Basket Analysis, Frequently Bundled Products and more. Use Case(s): Average value of all cars in U.S.
In the final section of this article, we will discuss the considerations for solution selection but, for now, it is worth mentioning that your team members will want to use business intelligence reporting, dashboards, key performance indicators (KPIs), automated alerts, etc.,
We believe that our focus on self-serve data preparation and our product roadmap assures the continued evolution and advancement of data democratization, and business user data literacy.
By integrating this approach within the business intelligence and augmented analytics environment the business can eliminate the need for expert programmers and IT professionals and allow team members to perform simple analytical, reporting and visualization tasks and create and explore analytics without the assistance of consultants or IT staff.
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content