![]() The reduced size of columns, result in a smaller amount of disk I/O operations and therefore it improves query performance. However, data is something that changes with time and a decision that made sense a few months ago, might not be the optimal one anymore.ĭata is something that changes with time and a decision that made sense a few months ago, might not be the optimal one anymore.įor this reason, we prefer to include Column Compression Settings as part of cluster maintenance, identifying again how the work of a data analyst can drive the related choices more efficiently.Īmazon Redshift is a columnar database, and the compression of columns can significantly affect the performance of queries. Why is Column Compression Important?Ĭhoosing the appropriate Column Compression Encoding is usually perceived as a choice made during the process of design the tables of a database. This choice is largely driven by the nature of the data that the column holds. Such improvement can happen by selecting an appropriate Column Compression Encoding. ![]() In this chapter, we are going to see how to use this knowledge to optimize an Amazon Redshift Cluster and improve the query performance. During these tasks, the data analyst tries to further understand the data. What they can achieve with the data in analytic terms and how it should be organized to achieve their analytic goals. Data cleaning and preparation are among the most time consuming parts of a Data Analyst or Data Scientist’s job.
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