A leading global provider of news and information services
Data Architecture, Data Management, Data Platform, Legacy Modernization, BI & Data Analytics


Our client, the world’s leading provider of news and information services to financial institutions, was grappling with their outdated financial data analytics platform. Integrating real-time financial news, SEC information, and market forecasting capabilities, this platform was essential for managing asset portfolios for their customers that included top financial institutions like the Royal Bank of Canada and US Trust. However, it was plagued with issues: 1. Fragmented Development History: The platform was a patchwork of different teams' efforts, each using their own set of database rules and technological frameworks. This disjointed development history led to significant data inconsistency and prohibitively expensive support. 2. Compromised Analytics: The data inconsistency became a major hurdle in performing comprehensive analytics. Retrieving data for accurate market forecasting was also a challenging process, along with an assessment of consultant performance and the accuracy of forecasts. 3. Scalability Roadblocks: Its architecture was not built for growth. As market demands evolved, scaling up the system required integrating new, intricate components into an already complex architecture. Faced with these challenges, the client sought a partner who could not only conduct a thorough audit of their existing data ecosystem but also guide them in establishing a modern data architecture. The goal was to revamp their data warehouse and create a new, robust data analytics platform, informed by insights from the in-depth audit.

Our mission
Our journey with the client began with a focused mission. We first assembled a dedicated team to handle custom development for specific analytics needs. This included creating unique consensus forecast mechanisms in line with individual customer requirements. As our partnership grew, so did our role. We evolved into subject matter experts, extending our services to encompass development and support for the client's entire user base. Our team expanded from five to dozens of people to meet these new demands. This growing trust led to our key project: a comprehensive audit of the client’s entire data ecosystem, followed by the development of a cutting-edge data analytics platform tailored for the financial sector. Our objectives were:
Overhaul the existing data architecture to meet current standards of efficiency and capability
Streamline diverse technological components into a cohesive, integrated tech stack
Create a new financial data analytics platform that was not only scalable but also cost-efficient, enabling the client to manage growth effectively

Our approach

In the course of auditing the client’s data and building an advanced data analytics platform, we undertook the following key steps:
In-Depth Business Analysis: - Conducted a comprehensive audit of business processes and systems - Engaged with numerous stakeholders to deeply understand data-related goals, needs, and complex business rules governing the client’s analytics
Data Ecosystem Assessment: - Performed a detailed analysis to understand all data flowing within the platform - Conducted a thorough audit of the existing data ecosystem, including data types, sources, flows, and integrations - Identified data silos, inconsistencies, and gaps in data governance
Data Warehouse Development: - Designed and implemented a robust, scalable data warehouse infrastructure for aggregating all data (client portfolios, market indicators, company financials, etc.) - Utilized extract, transform and load (ETL) processes to integrate diverse datasets
Data Standardization and Integration: - Established data models to ensure consistency and interoperability of data sources to make them available for more clients - Implemented data cleansing and transformation techniques to normalize disparate data formats
Data Management Strategy: - Designed and implemented a comprehensive data management strategy, including rules for data storage, updating, removal, and processing - Focused on aligning data management with business objectives and client needs
Custom Analytics and Recommendations: - Integrated advanced analytics and built a dedicated analytics storage system
Continuous Collaboration and Expertise: - Maintained ongoing communication with stakeholders to refine and adapt strategies - Leveraged our expertise as subject matter experts to drive platform development and client satisfaction
financial data analytics platform
data analytics platform for finance


Our financial data analytics solution significantly improved the platform's scalability, enabling the client to expand their services to a broader range of financial institutions and launch mass-market products
The new analytics platform improved data accuracy and efficiency, yielding more reliable analytics and insights
Its intuitive and responsive user experience increased client satisfaction and retention rates
By unifying the tech stack and streamlining data processes, we also achieved considerable cost-effectiveness in operations

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