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Discover how our tailored data strategies helped streamline operations, improve visibility, and turn complexity into actionable intelligence.
Transforming Data Challenges into Strategic Insights
The Problem
In the face of rapid growth, our client encountered a significant data management challenge, with diverse data models impeding effective analytics. Custom SQL for each model led to time-intensive development and unreliable results due to the complexity of managing numerous models.
In the face of rapid expansion, our client encountered a substantial influx of data organized across diverse models. This data structuring variation necessitated the creation of custom SQL queries for each model to conduct comprehensive company analytics. However, this approach became unsustainable over time. Basic analytics required excessive development efforts, and the complexity of multiple models often resulted in unreliable outcomes.
The Solution
To address these issues, our team at SEQTEK performed a comprehensive assessment and proposed a data warehouse as the key solution. We designed a unified data model by integrating requirements from over a hundred distinct models. Through an Extract, Transform, Load (ETL) process, we consolidated these models into a centralized data warehouse, providing a tailored storage solution.
The Impact
Centralizing data storage streamlined development efforts, resulting in a reliable and accurate reporting solution. Embraced by business users, this enhanced efficiency and productivity across the organization. Furthermore, the new data infrastructure positioned the client for future integration of Artificial Intelligence (AI) on a singular data model, anticipating long-term advancements and maintaining a competitive edge.
Transforming Data Challenges into Strategic Insights
Discover how our tailored data strategies helped streamline operations, improve visibility, and turn complexity into actionable intelligence.
The Problem
In the face of rapid growth, our client encountered a significant data management challenge, with diverse data models impeding effective analytics. Custom SQL for each model led to time-intensive development and unreliable results due to the complexity of managing numerous models.
In the face of rapid expansion, our client encountered a substantial influx of data organized across diverse models. This data structuring variation necessitated the creation of custom SQL queries for each model to conduct comprehensive company analytics. However, this approach became unsustainable over time. Basic analytics required excessive development efforts, and the complexity of multiple models often resulted in unreliable outcomes.
The Solution
To address these issues, our team at SEQTEK performed a comprehensive assessment and proposed a data warehouse as the key solution. We designed a unified data model by integrating requirements from over a hundred distinct models. Through an Extract, Transform, Load (ETL) process, we consolidated these models into a centralized data warehouse, providing a tailored storage solution.
The Impact
Centralizing data storage streamlined development efforts, resulting in a reliable and accurate reporting solution. Embraced by business users, this enhanced efficiency and productivity across the organization. Furthermore, the new data infrastructure positioned the client for future integration of Artificial Intelligence (AI) on a singular data model, anticipating long-term advancements and maintaining a competitive edge.