February 2022 Summaries

HomeToGo's Engineering blog explores a strategy to monitor the usage of Superset, their chosen reporting tool, by leveraging its internal metadata database. Seeking to streamline their data tech stack, HomeToGo transitioned from using multiple tools like Tableau and Redash to Apache Superset for its visual data exploration capabilities and robust SQL features. The article details the process of connecting Superset to its PostgreSQL metadata database to track user adoption rates and usage patterns as part of a hackathon project. This involved creating custom datasets and dashboards to analyze key metrics such as user activity, chart type usage, and adherence to naming conventions. The initiative aims to enhance user engagement, optimize data models, and maintain organized data environments, while also inviting contributions from the community for further improvements in classifying user actions and exploring performance metrics.

CrateDB is a versatile, open-source database adept at handling diverse data types like time-series, full-text search, geospatial, and structured or semi-structured data, and it offers SQL compatibility and easy integration. This tutorial illustrates the process of building a Superset dashboard powered by CrateDB, focusing on visualizing a power consumption dataset from Avignon, France, that details electricity usage across several years for different household utilities. It guides users through installing CrateDB, importing the dataset, and using Superset to create visualizations such as maps and graphs to analyze energy consumption patterns. The tutorial emphasizes the use of calculated columns in Superset to separate latitude and longitude data for better geospatial visualization and provides a step-by-step approach to creating various charts, including a time-series area chart to depict monthly energy usage by type. The tutorial concludes with tips on customizing and expanding the dashboard, offering resources for further exploration of CrateDB and Superset functionalities.

Apache Superset, an open-source data exploration and visualization tool, is widely used by enterprises like Airbnb, Lyft, and Nielsen to derive business value from large datasets. In the context of YugabyteDB, a distributed SQL database compatible with PostgreSQL, Superset enables users to seamlessly explore and visualize data using the standard PostgreSQL connector. The post provides a step-by-step demonstration of how business users can leverage Superset to gain insights from data stored in YugabyteDB, using a retail operations use case to track order processing efficiency. The process involves installing YugabyteDB, loading the Northwind database, setting up Superset, and connecting it to the database. Users can then explore datasets, create visualizations, and build dashboards to analyze order processing timelines and distribution by regions. This integration of YugabyteDB and Superset supports enterprises in their digital transformation efforts by facilitating the creation of business value from extensive data collections, backed by strong documentation and community support.