STOCK DATA VISUALIZATION PLATFORM
The project develops in the context of banking, finance, insurance and services for institutional investors. The industry is constantly changing as a result of market changes but above all of the deep technological innovation that has led to the digitalization of economic activities and, with access to Big Data and related processing technologies, has created new development opportunities.
The client deals with consulting and Fintech solutions to support the innovation of the business models of the BFSI market. Among the industry leaders, it responds to the main business challenges by offering innovative software solutions for analytics, reporting and data management for Risk Assessment.
Providing innovative solutions that allow rapid interpretation of large amounts of data in order to make decision-making more effective is the main challenge that the customer finds himself facing.
In this specific case, the need is to structure a tool for analyzing the performance of shares based on a monitoring and aggregation system of a considerable amount of information from various sources.
The particular focus requested by the customer is on an efficient and customized data visualization system that allows an effective interpretation of trends, outliers and patterns.
In order to meet the expressed need, we have created a web platform able to aggregate data in different ways and to display them through multiple customized graphic representations such as:
Stream Graph, time stream divided by category
Map, geographical distribution
Graph, representation of relations
Tag Cloud, distribution by keyword
Each representation has been made interactive and configurable.
The information present in the database has been characterized on different parameters such as category and company and can be filtered through a search engine and tree representation.
A notification and data sharing system via email has also been integrated.
Improvement of efficiency in data interpretation
better interaction with the data
better customization of views
Optimization of insights sharing with stakeholders
greater speed in the transmission of information
greater efficiency in receiving warnings
Faster recognition of new trends and anomalies
The following technologies were used:
Client: TypeScript + Angular + D3
Data Processing Pipeline
The web client took care of requesting the data from the server and displaying them correctly in the various screens, the server of exposing the API Rest to the client and executing the queries on ElasticSearch.
Team: Project Manager, Business Analyst, Front-end Developer, Back-end Developer
Duration: 3 month