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Many healthcare providers still rely on outdated flat files for data exchange, requiring IT and data integration teams to construct complex pipelines and convert EHR/EMR data into FHIR resources. This process is time-consuming, expensive, and difficult to maintain. Discover a simpler solution with Datuum.ai, automating the mapping process for smoother interoperability and cost savings.

Data integration presents challenges in diverse data sources and mixed tool sets. In this article, we address these hurdles and provide strategies to overcome them, enabling organizations to leverage data effectively in a data-driven world.

Extracting data from existing databases is a complex task the Data Engineering team handles. Legacy systems present additional challenges, such as inconsistent data modeling and limited documentation. Despite these obstacles, quick results are expected. This article shares insights and tips to navigate these challenges and save time.

Customer onboarding is a crucial aspect of any business’s success, and it is widely acknowledged that companies that prioritize customer onboarding can experience significant benefits, such as higher customer retention rates, increased revenue growth, and better customer satisfaction.

Data Engineering is crucial for modern businesses, enabling organizations to turn their data into actionable insights. However, many organizations face a significant disconnect between their Business and Data Engineering teams.

Datuum.ai will be pitching its data integration platform from the biggest stage of the TechChill event in Riga.

Shadowbox has partnered with Datuum.ai to enhance its Electronic Health Record (EHR) interface automation with a robust, fast-mapping technology powered by Datuum.ai’s artificial intelligence (AI) data integration platform.

The abundance of tabular data being accumulated by enterprises internally and online represents a big challenge for data integration and analysis for companies that strive to be data-driven.