Introduction
Azure Data Explorer's web UI helps you consume and explore data. You can use Azure Data Explorer to collect, store, and analyze diverse data to gain insights and make data-informed decisions. Here, you'll learn how to begin exploring a new dataset in Azure Data Explorer web UI.
Example scenario
Suppose you're a weather enthusiast with a passion for data science. You've come across a new dataset that contains information about storms in the US. You aren't familiar with this dataset, so you don't yet know what kinds of analyses you can do and questions you can ask with this data. You'd like to get a sense of how the data is structured, and what range of information is present. You'll then share these initial insights with your weather-enthusiast friends.
What will we be doing?
Here, you'll explore an unfamiliar dataset by characterizing the dataset structure and range, visualizing the data distribution, and sharing these insights with others.
While this module uses some queries in Kusto Query Language to characterize the data, writing complex queries is outside the scope of this module. To learn more about Kusto Query Language itself, see Write your first query with Kusto Query Language.
What is the main goal?
By the end of this session, you'll be able to identify the schema, range, and completeness of an unfamiliar dataset using Azure Data Explorer.