STOCK DATA VISUALIZATION PLATFORM
Industry
#finance
Business Value
#stock-analysis
#data-aggregation
Tech
#data-visualization
#reactive-web-platform
#advance-analytics
Context
The project is situated within the banking, finance, insurance, and institutional investor services sector. This industry experiences continuous evolution due to market dynamics and, more significantly, the profound technological innovations that have led to the digitization of economic activities. The access to Big Data and related processing technologies has opened up new avenues for development
Our client specializes in providing consulting and Fintech solutions to drive innovation within the business models of the BFSI (Banking, Finance, and Insurance) market. As a leader in the industry, they address the primary business challenges by delivering innovative software solutions for analytics, reporting, and data management to facilitate risk assessment.
Challenge
The primary challenge facing our customer is the provision of innovative solutions that enable the rapid interpretation of vast amounts of data to enhance decision-making effectiveness.
In this specific case, the requirement is to develop a tool for analyzing share performance based on a monitoring and aggregation system that assimilates a substantial volume of information from diverse sources.
The customer has placed a particular emphasis on the development of an efficient and customized data visualization system. This system should facilitate the effective interpretation of trends, identification of outliers, and recognition of patterns.
Solution
To address the stated requirement, we developed a web platform capable of aggregating data in various ways and presenting them through multiple customized graphical representations, including:
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Stream Graph, a time-based stream divided by category
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Map, geographical distribution
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Graph, representation of relationships
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Tag Cloud, distribution based on keywords
Each of these representations has been designed to be interactive and configurable.
The data in the database have been categorized based on various parameters such as category and company, and users can apply filters using a search engine and tree representation.
Additionally, we integrated a notification and data sharing system via email.
Value
Enhanced efficiency in data interpretation:
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Improved interaction with data
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Enhanced customization of views
Streamlined sharing of insights with stakeholders:
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Accelerated information transmission
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Increased efficiency in receiving alerts
Expedited identification of new trends and anomalies
Tech
The following technologies were used:
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Client: TypeScript + Angular + D3
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Server: JavaScript + NodeJS
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Database: ElasticSearch
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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.
Project details
Team: Project Manager, Business Analyst, Front-end Developer, Back-end Developer
Methodology: Scrum
Duration: 3 month