Industry:
Healthcare and technologies
Technology stack:
Our client is a global alliance of healthcare and technology companies with a shared mission to digitize health data and use AI to derive insights.
Their long-term goal is to create data-driven healthcare products, including web/mobile apps, medical devices, and customer-oriented gadgets, that empower patients to manage their health and improve healthcare delivery. The focus is on innovation through collaboration, leveraging cutting-edge technology to transform the way we approach healthcare.
The customer approached us with a significant challenge - they had amassed a vast amount of data over a prolonged period of time, which was dispersed across multiple locations. Unfortunately, this data was not being utilized for business insights or decision-making purposes, which was hindering their ability to optimize their operations fully.
To address this issue, our customer needed to create several types of central data repository that would support data exploration and analytics workloads, while also serving as a source for other repositories. It was essential to catalog and govern the data, ensuring its quality remained manageable.
Our team collaborated closely with the customer to create a comprehensive solution that leveraged advanced data management strategies and cutting-edge technology. This enabled our customer to build a centralized repository that served as a reliable source of information for their analytics and reporting needs.
We built a centralized data repository consisting of a Data Lake (DL) and a Data Warehouse (DWH). The DL was designed to store non-structured and semi-structured information, as well as raw structured data from individual products, while the DWH functioned as a repository of well-prepared, trusted datasets for data analysis and self-service analytics.
To ensure effective data governance and successful implementation of these repositories, we conducted a company-wide assessment utilizing the Stanford Maturity model approach. The results of the assessment informed the development of a "Data governance layer," which encompassed a set of best practices and processes to enable the customer to catalog existing data across the DL.
Critical processes such as metadata management, data audit, data lineage, and data quality control were implemented to ensure effective governance of the repositories. These processes ensured that the data was accurately cataloged, audited, and managed effectively, providing the customer with the confidence to make data-driven decisions.
The implementation of the data management solution had a significant positive impact on the customer's business operations. The Data Lake and Data Warehouse repositories enabled the customer to store and manage large volumes of data from various sources, facilitating in-depth analysis and reporting. Our "Data governance layer" ensured that the data was accurately cataloged and managed, providing reliable and accurate insights for better decision-making, increased efficiency, and enhanced reporting capabilities.
Overall, our team was able to provide the customer with a comprehensive solution that included building a reliable centralized data repository, as well as implementing critical data governance processes. By doing so, we enabled the customer to effectively manage their data and unlock valuable insights, positioning them for success both now and in the future.