September 2020 Summaries

The blog post, part of a three-part series, details the process of building a Slack community dashboard using open-source tools. It emphasizes the use of Meltano, an ELT platform combining Singer and dbt, to extract data from Slack, transform it, and load it into a Postgres database. The post guides readers through setting up a Slack API, installing and configuring Meltano, and using the tap-slack extractor to pull data from Slack channels. It illustrates how to manage OAuth tokens and configure extraction settings to sync Slack data incrementally. The post concludes with a preview of a future installment that will focus on building a dashboard in Apache Superset to visualize the extracted data, highlighting the potential for insights into community growth and health.

Preset has launched a new documentation site for Apache Superset and Preset Cloud users, aimed at enhancing productivity and success through comprehensive guides and tutorials. The site is organized into six categories, including Getting Started, Connecting Your Data, Creating Datasets, Creating a Chart, Creating a Dashboard, and Sharing and Collaboration. These resources provide step-by-step instructions on tasks such as integrating various data sources, building datasets, visualizations, and dashboards, and facilitate teamwork through sharing and collaboration features. Preset aims to deliver the best experience for its community and encourages user feedback to continually improve the documentation and overall user experience.