What is data analytics?
Data analytics is the process of analyzing raw data using statistical methods, algorithms, and tools to extract meaningful insights.
Data analytics is the work of turning raw data into answers a business can act on: collecting it, cleaning it, modeling it and reading what it says.
The four types of data analytics
The four types of data analytics
- Descriptive: what happened, such as last month’s revenue by channel.
- Diagnostic: why it happened, such as which campaign drove the drop.
- Predictive: what is likely to happen, such as next quarter’s demand.
- Prescriptive: what to do about it, such as where to move budget.
How it works
Most analytics follows the same path: define the question, collect the data, prepare it, analyze it and deliver the result to the people who decide. The data analysis process walks through each step.
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Why the definition matters
Two analysts can start from the same data and report different numbers, because “revenue” or “active user” was defined differently. Agreeing on those definitions once, in a shared model, is what makes the numbers trustworthy.
For the types in depth, what a data analyst does and why numbers disagree, read What is data analytics?.
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