1. Front-End Development
JavaScript/TypeScript: Core language skills for implementing interactive features, managing state, and handling events.
React.js/Next.js: Knowledge of React, a popular JavaScript library for building user interfaces, and Next.js, a framework for server-side rendering and static site generation.
HTML/CSS: Proficiency in HTML and CSS for structuring the content and styling the network visualization and UI components.
Component Libraries: Familiarity with component libraries like Material-UI or Bootstrap to implement consistent, responsive design elements.
2. Data Visualization
D3.js: Understanding of D3.js (Data-Driven Documents), a powerful library for creating dynamic and interactive data visualizations, which is often used for network graphs.
Chart.js, Recharts, or Highcharts: Experience with other charting libraries can be helpful for building complementary visualizations (e.g., scatter plots, bar charts).
Canvas/SVG: Knowledge of rendering techniques like Canvas or SVG for drawing and animating complex graphical elements in the browser.
Graph Theory: Understanding basic graph theory, which is crucial for representing and manipulating networks (nodes and edges) effectively.
3. Back-End Development
Node.js/Express.js: Knowledge of back-end JavaScript environments like Node.js and frameworks like Express.js for handling API requests, data processing, and server-side logic.
APIs: Experience designing and consuming RESTful APIs or GraphQL to fetch and manipulate data from the server.
Database Management: Familiarity with databases (SQL or NoSQL) for storing, retrieving, and querying the large datasets that often underpin complex networks.
4. Data Management and Processing
Data Modeling: Skill in modeling complex relationships in data, which is critical for representing entities and their interconnections in a network.
Big Data Technologies: Familiarity with big data tools and technologies (e.g., Hadoop, Spark) may be necessary for handling very large datasets.
5. Advanced JavaScript Concepts
Asynchronous Programming: Expertise in handling asynchronous operations, such as fetching data from APIs or processing large datasets without blocking the user interface.
Event-Driven Programming: Ability to manage user interactions (e.g., clicks, hovers) effectively, which is crucial in a dynamic network visualization.
We help businesses unify their data, get contextual insights, and make accurate decisions. Our platform analyses all of the people, places, organizations, policies, and rules within your internal and multiple external datasets to make contextual decisions and recommendations across multiple vertical apps such as supply chain, ESG, customer insights, financial crime, and fraud serving financial services, healthcare, manufacturing firms, and governments.
We use cutting-edge AI to provide vertical app solutions.