Summary
In this chapter, you learned about different ways to work with data in Azure Synapse Data Explorer. The Data Explorer engine stores and manages large volumes of data efficiently, and this chapter helped you understand how to make sense of the data you have on Data Explorer pools using the different tools available for data exploration with Azure Synapse workspaces.
First, you used different KQL queries to navigate through your data and get familiar with the drone telemetry dataset. You created calculated columns, plotted information on charts using only the query editor, and then explored your data by looking at percentiles. You then created a time series and used the native features of KQL to detect outliers in your data, and even analyzed the trends in your data using linear regression.
Next, you used Azure Synapse notebooks to explore data using Python. You created your first Apache Spark pool, used it to read data from our Data Explorer pool, and used different Python...