sunburst tech

notes:

• plot with d3 library and python
• worth opening in another tab since it’s pretty big, not best rendered here
• this is a static export (svg), but i make use of this in an interactive html version… not sure how to add it here yet
  • tbd! XXX

Programming Languages

• ➤ Data Science: Languages commonly used for data analysis, statistics, and scientific computing.
• ➤ Data Engineering: Building and managing systems and pipelines to process and prepare data for analysis and use.
• ➤ Relational Database Lang: Languages designed for querying and managing data in relational databases.
• ➤ System Programming: Languages suited for building operating systems, drivers, and high-performance applications.
• ➤ Mobile: Languages primarily used for developing mobile applications.
• ➤ Web Development: Languages used for building dynamic websites and web applications.
• ➤ Frontend Lang: Languages and preprocessors for building and styling user interfaces in web browsers.
• ➤ Enterprise: Languages widely adopted in large-scale business and enterprise applications.
• ➤ Scientific Computing: Languages tailored for complex mathematical, engineering, or scientific tasks.
• ➤ Scripting: Languages used for automating tasks and writing command-line scripts.

➤ Data Science

• R Language: A statistical programming language widely used for data analysis and visualization.
• Python: A popular, easy-to-learn programming language used for web, data science, and automation.

➤ Data Engineering

• Scala: A language combining object-oriented and functional programming, often used with Apache Spark.

➤ Relational Database Lang

• SQL: A standard language for managing and querying relational databases.

➤ System Programming

• RUST: A modern, high-performance systems programming language focused on safety and concurrency.
• GO: A statically typed programming language by Google, known for simplicity and concurrency.
• C++: A high-performance, general-purpose programming language with object-oriented features.
• C: A foundational, procedural programming language used for system and application software.

➤ Mobile

• Kotlin (Android): A modern programming language for Android app development, interoperable with Java.
• Swift (iOS): Apple’s modern programming language for iOS, macOS, and other Apple platforms.
• Objective-C: A legacy programming language for iOS and macOS development.

➤ Web Development

• Ruby: A dynamic, object-oriented programming language often used for web development.
• PHP: A widely-used server-side scripting language for web development.
• JavaScript: The core scripting language for dynamic content on web pages.

➤ Frontend Lang

• SASS: A CSS preprocessor that adds variables, nesting, and more to standard CSS.
• TypeScript: A typed superset of JavaScript that compiles to plain JavaScript.
• HTML: The standard markup language for creating web pages and web applications.
• CSS: The language used to style and layout web pages.

➤ Enterprise

• Java: A versatile, object-oriented programming language used in enterprise, web, and Android apps.
• C#/.Net: Microsoft’s modern, object-oriented programming language and framework for Windows and web.

➤ Scientific Computing

• MATLAB: A high-level language and environment for numerical computing and visualization.

➤ Scripting

• Shell/Bash: A command-line scripting language for Unix-based systems, essential for automation and DevOps.

Frameworks & Libraries

Reusable code libraries and frameworks for building applications efficiently.

• ➤ Backend: Frameworks and libraries for server-side application development.
• ➤ Frontend: Frameworks and libraries for building interactive user interfaces and single-page applications.

➤ Backend

• Flask: A lightweight Python web framework for building web applications and APIs.
• ASP.NET: A Microsoft framework for building web applications and services with .NET.
• django: A high-level Python web framework that encourages rapid development and clean design.
• Node.js: A JavaScript runtime for building scalable server-side and networking applications.
• Laravel: A PHP web application framework with expressive, elegant syntax.
• Ruby on Rails: A full-stack web application framework written in Ruby.
• Spring Boot: A framework for building production-ready Java applications quickly and easily.
• Express.js: A minimal and flexible Node.js web application framework for APIs and web apps.

➤ Frontend

• React.js: A JavaScript library for building interactive user interfaces, mainly for web apps.
• Angular: A TypeScript-based front-end framework for building dynamic web applications.
• Next.js: A React-based framework for building server-side rendered and static web applications.
• Vue.js: A progressive JavaScript framework for building user interfaces and single-page applications.
• jQuery: A fast, small JavaScript library that simplifies HTML document traversal and manipulation.
• Alpine.js: A minimal JavaScript framework for composing behavior directly in your HTML.
• PReact: A fast, lightweight alternative to React for building web interfaces.

Databases

Systems for storing, managing, and retrieving structured or unstructured data.

• ➤ NoSQL: Databases designed for flexible, scalable storage of unstructured or semi-structured data.
• ➤ Relational Database: Databases that store data in structured tables with defined relationships.
• ➤ Cloud Data Warehouse: Cloud-based platforms optimized for large-scale analytics and data storage.
• ➤ In-Memory Database: Databases that store data in RAM for ultra-fast access.
• ➤ Search Engine: Databases optimized for full-text search and analytics.

➤ NoSQL

• MongoDB: A popular NoSQL document-oriented database for scalable applications.

➤ Relational Database

• SQLLite: A lightweight, file-based relational database engine often used in embedded applications.
• Oracle: A powerful, enterprise-grade relational database management system.
• MySQL: A widely-used open-source relational database management system.
• PostGreSQL: An advanced open-source relational database known for extensibility and standards compliance.
• Microsoft SQL Server: A widely used enterprise-grade relational database management system from Microsoft.

➤ Cloud Data Warehouse

• Snowflake: A cloud-native data warehouse platform for scalable analytics and data sharing.
• Google BigQuery
• Amazon RedShift
• Not Warehouse, but more like Data Lake
  • Amazon S3
  • Google Cloud Storage
  • Azure Data Lake Storage
• And Data Lakehouse:
  • Databricks

➤ In-Memory Database

• Redis: An open-source, in-memory key-value store used for caching and real-time analytics.

➤ Search Engine

• Elasticsearch: A distributed, RESTful search and analytics engine for all types of data.

Data Analytics & Viz

Software for analyzing, processing, and visualizing data.

• ➤ Business Intelligence: Tools for transforming data into actionable insights and reports.
• ➤ Big Data: Platforms for processing and analyzing massive datasets.
• ➤ Stream Processing: Tools for processing real-time data streams.
• ➤ Visualization: Tools for creating interactive charts, dashboards, and visual data representations.

➤ Business Intelligence

• PowerBI: A Microsoft tool for interactive data visualization and business intelligence reporting.
• Tableau: A leading data visualization and business intelligence platform.
• Looker: A modern business intelligence and analytics platform from Google Cloud.
• Qlik Sense: A self-service data analytics and visualization tool.
• Streamlit: Open-source python framework to build interactive web apps for DS and ML.

➤ Big Data

• Apache Spark: An open-source analytics engine for large-scale data processing and machine learning.
• Hadoop: An open-source framework for distributed storage and processing of big data.
• Splunk: A platform for searching, monitoring, and analyzing machine-generated big data.

➤ Stream Processing

• Kafka: A distributed streaming platform for building real-time data pipelines and applications.

➤ Visualization

• Grafana: An open-source platform for monitoring and observability with rich dashboarding capabilities.

Cloud Platforms & Services

Platforms offering cloud computing, storage, and application hosting services.

• ➤ Cloud: General-purpose cloud computing platforms for hosting and scaling applications.
• ➤ Web Infrastructure: Cloud services focused on deployment, automation, and infrastructure management.
• ➤ Mobile Backend: Cloud services for building and managing mobile app backends.

➤ Cloud

• Azure: Microsoft’s cloud computing platform offering a wide range of services.
• Google Cloud: Google’s suite of cloud computing services and infrastructure.
• heroku: A cloud platform that enables easy deployment and scaling of web applications.
• AWS: Amazon Web Services, the leading global cloud computing platform with a vast range of services.
• IBM Cloud: IBM’s cloud computing platform for enterprise and hybrid cloud solutions.
• Oracle Cloud: Oracle’s cloud platform, optimized for Oracle workloads and enterprise applications.

➤ Web Infrastructure

• CloudFare: A web infrastructure and security company offering CDN, DNS, and DDoS protection services.
• Netlify: A cloud platform for automating deployment and hosting of modern web projects.

➤ Mobile Backend

• Firebase: A platform by Google for building and scaling mobile and web applications.

Cloud native

Cloud native is building and running scalable apps optimized for the cloud using containers and microservices.

• ➤ Containerization: Technologies for packaging applications and their dependencies into isolated containers.
• ➤ Orchestration: Tools for automating deployment, scaling, and management of containerized applications.

➤ Containerization

• Docker: A platform for developing, shipping, and running applications in containers.

➤ Orchestration

• Kubernetes: An open-source system for automating deployment, scaling, and management of containerized apps.

DevOps & Automation

Tools for automating software development, deployment, and infrastructure management.

• ➤ Infrastructure as Code: Tools for managing infrastructure using code and automation.
• ➤ Configuration Management: Tools for automating the setup and maintenance of software environments.
• ➤ CI/CD: Tools for continuous integration and continuous delivery of software.
• ➤ Testing: Tools for automating software and web application testing.
• ➤ Monitoring: Tools for tracking the health and performance of applications and infrastructure.

➤ Infrastructure as Code

• Terraform: An open-source tool for provisioning and managing cloud infrastructure as code.

➤ Configuration Management

• Ansible: An automation tool for configuration management, application deployment, and task automation.
• Puppet: A tool for automating the management and configuration of infrastructure.

➤ CI/CD

• Jenkins: The most popular open-source automation server for continuous integration and delivery.
• GitHub Actions: A CI/CD platform integrated with GitHub for automating software workflows.

➤ Testing

• Selenium: A leading open-source tool for automating web browser testing.

➤ Monitoring

• Prometheus: An open-source system for monitoring and alerting, designed for reliability and scalability.

Other

Technologies that don’t fit traditional categories but are widely used in the industry.

• ➤ Game Development: Platforms and tools for building interactive games and simulations.
• ➤ Machine Learning: Frameworks and libraries for building and deploying machine learning models.

➤ Game Development

• Unity: A leading platform for creating and operating interactive, real-time 3D content.

➤ Machine Learning

• TensorFlow: An open-source machine learning framework developed by Google.

OS & Robotics

Platforms and frameworks for building operating systems and robotics applications.

• ➤ Robotics: Frameworks and tools for developing robotic systems and automation.

➤ Robotics

• ROS: An open-source framework for developing robot software and managing robotic systems.