In data analytics, data fundamentally refers to facts and statistics collected together for reference or analysis. It is the essential raw material that fuels the entire process of data analytics.
The Role of Data in Analytics
Data serves as the foundation upon which data analytics is built. As the science of analyzing raw data to make conclusions, data analytics relies entirely on having facts and statistics available to examine. Without collected data, there is nothing to analyze.
Think of data as the ingredients for a recipe. Data analytics is the process of combining, preparing, and interpreting those ingredients (data) to create a final dish (insights and conclusions).
Key Definitions
According to CompTIA's guide on data analytics, the key terms are defined as follows:
| Term | Definition |
|---|---|
| Data | Facts and statistics collected together for reference or analysis. |
| Data analytics | The science of analyzing raw data to make conclusions about that information. |
Source: CompTIA's Key Terms Related to Data Analytics
These definitions highlight the intrinsic link: data is the input, and data analytics is the process applied to that input to derive meaningful conclusions.
Types of Data
While the core definition is facts and statistics, data can come in many forms in the real world, such as:
- Numerical values (sales figures, temperatures, ages)
- Text (customer reviews, social media posts)
- Categorical information (product types, locations, demographics)
- Images and videos
- Sensor readings
- Website clickstreams
Regardless of the specific type or source, data must be collected and prepared to be suitable for analytical processes aimed at uncovering insights.
In summary, data in data analytics is the set of facts and statistics that are gathered to be studied and interpreted, allowing analysts to draw informed conclusions and make decisions based on the information contained within that data.
