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Rapid declines in the cost of sequencing have made large volumes of DNA sequence data available to individual investigators. Now, data analysis is the rate-limiting step: providing a user with sequences alone typically leads to bewilderment, frustration, and skepticism about the technology. In this talk, I focus on how to extract insights from 16S rRNA data, including key lab steps (barcoding and normalization) and on which tools are available to perform routine but essential processing steps such as denoising, chimera detection, taxonomy assignment, and diversity analyses (including detection of biological clusters and gradients in the samples). Providing users with advice on these points and with a standard pipeline they can exploit (but modify if circumstances require) can greatly accelerate the rate of understanding, publication, and acquisition of funding for further studies.