In the course of auditing the client’s data and building an advanced data analytics platform, we undertook the following key steps:
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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
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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
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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
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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
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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
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Custom Analytics and Recommendations:
- Integrated advanced analytics and built a dedicated analytics storage system
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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