Multi-omic projects provide new insights into the function and composition of the microbial world one study at a time. However, to understand relationships across studies we must aggregate them into meta-analyses to identify features reproducible across biospecimens and data layers, and generate new hypothesis. Qiita (qiita.microbio.me) dramatically accelerates such integration tasks in an open source web-based platform for the analysis and comparison of microbiome studies. Currently, Qiita provides 3 main analytical components: alpha (diversity within a sample), beta (diversity differences between samples) and taxonomy (taxonomic composition of samples); via QIIME2 plugins. Qiita hosts over 350 public studies, with more than 185,000 samples ready to be combined, analyzed, downloaded and visualized. This easy aggregation and exploration of microbiome data allowed us to identify some of the current challenges for data analysis, retrieval, visualization and user analytical empowerment, which we will cover during this presentation.