Characterize data with Azure Data Explorer
What happens when you get a new dataset? Before you can run complex queries and gather deep insights from the data, you first need to know what kind of data you have available. Characterizing the data helps you understand what information you're looking at and what you can do with it.
Characterize the data
Suppose you're looking at an unfamiliar table of meteorological data. At first, you'll want to answer questions like:
- What information is part of this data?
- How many entries are in this table?
- What is the range of entries in this table?
- What types of data appear in the table?
- Is the dataset part of a time series?
- Is the dataset complete? Are there time or location gaps?
- How can grouping certain fields help me understand the data?
You can answer some of these questions by looking at a sample of the data. Some of these questions will require grouping—or aggregating—the data. Other questions are best answered by visualizing the results.