Major Technologies Used:
Challenges: A technology company providing solutions for skilled nursing home operators experienced significant problems with its Analytical Data Platform. The platform’s data pipelines were inefficient, struggling to handle complex data ingestion. Limited data insights resulted from poorly structured data and a lack of advanced analytics capabilities. Scalability and integration issues hampered the platform’s ability to support growth and seamlessly connect with existing applications. Finally, inconsistent data quality and weak governance controls created operational risks.
Our Solution: We conducted a thorough analysis of the client’s system and implemented a tailored solution to transform their data platform. We modernized data ingestion and architecture by redesigning data pipelines with Azure Data Factory and Python, building a robust data lake on ADLS and a star-schema SQL warehouse. Advanced data processing was implemented through a transformation engine using dbt and T-SQL for efficient data analysis. Integration and modeling were enhanced by developing a semantic layer with Cube.dev for seamless system integration and data modeling. Finally, data quality was ensured with Great Expectations and custom cataloging for improved governance and integrity. As a result, the revamped data platform delivered measurable benefits. Enhanced analytics capabilities provide a competitive edge, allowing the client to attract more clients and drive business growth. Operational efficiency increased due to streamlined workflows, which reduced overhead and improved overall productivity. Improved decision-making was enabled by advanced data visualization and robust data governance, allowing for confident data-driven choices.
Aeterna Technologies 