Neal Kaplan I'm a director of technical communications working for a data analysis startup in Redwood City. I started as a technical writer, and since then I've also been learning about information architecture, training, content strategy, and even something about customer support. I'm also passionate about cross-team collaboration and user communities.

What are different types of analytics tools?

1 min read

There are four main types of analytic tools. To help you determine which tools are right for your needs, here are descriptions.

What are 5 categories of analytic tools?

Depending on the stage of the data analysis, there are five main types.

What are analytics tools?

Data Analysts classify software and applications used by them to create and execute analytic processes that help businesses make smarter, more informed business decisions while minimizing cost and boosting profits.

What are the 4 types of analytics?

There are four types of analytic tools.

What are 3 different types of analytics?

There are three types of analytic tools that businesses use to make their decisions; descriptive, predictive and prescriptive.

What are different types of analytics?

Descriptive, Predictive and Prescriptive analytic solutions help companies make the most out of their big data. There is a different insight offered by each analytic type.

What are the 4 types of data analytics?

  • There is a descriptive analysis.
  • The analysis is called a Diagnostic Analysis.
  • There is a prediction of predictive analysis.
  • Prescriptive analysis of something.

Data can lead to better understanding of a business’s past performance and better decision-making for its future activities. The degree of difficulty and resources required increases as you move from the simplest type of analytics to more complex.

Descriptive analysis uses past data to answer what happened. Key Performance Indicators are the most used descriptive analysis in business.

Diagnostic analysis takes insights from descriptive analysis and drills down to find the causes of outcomes. As it creates more connections between data and identifies patterns of behavior, organizations use this type of analytics. Past data can be used to make predictions about the future.

Adding technology and manpower to forecast is needed for this analysis. The accuracy of predictions depends on quality and detailed data, which is why forecasting is only an estimate. Few organizations are capable of performing the final type of data analysis. Prescriptive analysis uses the latest technology and data practices.

There is no need for a human to do anything with artificial intelligence. More companies are entering the data-driven realm as technology continues to improve and more professionals are educated in data.

Neal Kaplan I'm a director of technical communications working for a data analysis startup in Redwood City. I started as a technical writer, and since then I've also been learning about information architecture, training, content strategy, and even something about customer support. I'm also passionate about cross-team collaboration and user communities.

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