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Book Overview & Buying
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Table Of Contents
Time Series Analysis with Spark
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So far, we have covered the foundations of time series and Apache Spark and the full lifecycle of a time series analysis project. In this chapter, we delve into the critical steps of organizing, cleaning, and transforming time series data for effective analysis. It covers techniques for handling missing values, dealing with outliers, and structuring data to suit Spark’s distributed computing model. This information is invaluable as it equips you with the skills to ensure data quality and compatibility with Spark, laying a robust foundation for accurate and efficient time series analysis. Proper data preparation enhances the reliability of subsequent analytical processes, making this chapter an essential prerequisite to derive meaningful insights from time-dependent datasets using Spark.
We’re going to cover the following main topics in this chapter: