February 2021 Summaries

ClickHouse is an open-source analytical database known for its speed, adopted by prominent companies such as Bloomberg, Cloudflare, eBay, Spotify, Uber, and CERN. It uses a columnar storage engine, which allows faster performance on analytical operations like AVG, DISTINCT, or MIN. The tutorial guides the reader through creating a dashboard on top of ClickHouse using Cube, an open-source analytical API platform. The author starts by running ClickHouse on various platforms, including macOS, Linux, AWS, GCP, and Yandex Cloud, before moving to building an analytical API with Cube.js. The author then explores data visualization options, including the Cube Developer Playground, which allows generating a schema, building queries, and visualizing results. Finally, the reader learns how to build a custom dashboard using React, ApexCharts, and Ant Design components to visualize stock market data from ClickHouse.

The author of the text highlights the diversity and variety of contributions made by members of open source communities, going beyond just code contributions. The author emphasizes the importance of recognizing and celebrating these contributions to foster a sense of community and motivate others to participate. A formal recognition program called "Heroes" is introduced, which aims to promote diversity and inclusivity among contributors. The Heroes are individuals who have made sustained contributions to the project and community over a 2-year term, with a limit of one Hero per organization. The program's primary goal is not to have as many Heroes as possible, but rather to grow the ranks gradually in line with the overall community size.

Data visualization is a crucial aspect of communicating insights from data. With numerous JavaScript frameworks and libraries available, choosing the right tool can be overwhelming. This post aims to help developers pick the right tool for their project by categorizing them into general-purpose charting libraries, low-level and complex dataviz tools, tables and data grids, timeline charts & time-based tools, geospatial and mapping tools, word clouds, and 3D visualization tools. The list includes popular frameworks such as Chart.js, Recharts, Highcharts, D3.js, Plotly.js, amCharts, Apache ECharts, Leaflet, Mapbox, and Three.js, among others. Each library is evaluated based on factors such as popularity, community size, licensing, and ease of use, providing a comprehensive guide for developers to select the best tool for their data visualization needs.

Cyndx is a company that uses AI-driven algorithms to help financial services companies identify emerging companies, growth opportunities, and investment opportunities. To enhance its data analytics capabilities, Cyndx expanded its platform by integrating with the business intelligence tool Cube. The company leverages Cube's React framework, visualization components, and API instance hosted on Google Kubernetes Engine for performance optimization. Cyndx also uses a custom backend to store permissions and dashboard configurations, ensuring personalized experiences for users. The team has implemented various testing protocols to ensure data quality, including browser testing with Datadog and 1,000 tests on data using dbt. Cyndx can self-host Cube and customize its appearance using React and CSS, making it an ideal choice for their platform. Looking ahead, the company plans to roll out self-serve analytics to its end-users, allowing them to create customized dashboards tailored to their individual needs and organization's workflows.