Three common analytics techniques in use

Below are three types of analytic techniques that are in use today.

• Regression - Used to estimate the relationship between sets of variables. One looks to see if there's a correlation, between a dependable and independant variables as well the impact of independent variables vs the dependent one, in order to identify trends, patterns and the like. This is useful for predicting trends.

• Cohort Analysis - Cohort Analysis is a subset of behavior analytics that takes data from a data set and breaks them into groups for analysis. These groups share common traits, experiences and results within a defined timespan.

• Sentiment Analysis - Many assume with data, it's just spreadsheets, Data and the like. But the thing about data is that it's value of qualitative data is overlooked. There's a lot of insight to gain from this type of data. One highly useful technique is Sentiment Analysis. The Process of sorting and understanding textual data. The goal is to interpret and classify the emotions conveyed within it. This enables one to learn how the company's customers feel about the various traits of a brand.  - (The 7 Most Useful Data Analysis Techniques [2022 Guide], 2022)

Bibliography 

CareerFoundry. 2022. The 7 Most Useful Data Analysis Techniques [2022 Guide]. [online] Available at: <https: careerfoundry.com="" en="" blog="" data-analytics="" data-analysis-techniques="" #:~:text="Descriptive%20analysis%2C%20which%20identifies%20what,make%20recommendations%20for%20the%20future"> [Accessed 21 May 2022].</https:>