Systems | Development | Analytics | API | Testing

Automating data extraction from patient registration forms in healthcare is crucial to enhancing patient care efficiency, accuracy, and overall quality. Over 71% of surveyed clinicians in the USA agreed that the volume of patient data available to them is overwhelming. This abundance of data highlights the importance of streamlining the extraction process. Manual extraction is time-consuming and prone to errors, hindering patient safety.

Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. For example, if there are separate clusters, and there are topics with the same purpose in the different clusters, then it is useful to aggregate the content into one topic.

An integration Platform as a Service (iPaaS) can be a game-changer for businesses looking to streamline operations and enhance efficiency. But with all the options available, how do you know which iPaaS to choose?

This add-on connector automatically extracts and incorporates metadata from Fivetran to reveal the upstream origins of the data in the destination database.

Did you know that the average enterprise utilizes over 1,500 APIs to drive its digital operations? APIs play a pivotal role in today’s data-driven landscape. However, few know the impact API architecture has in enhancing API performance.

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

Connecting multiple systems and exchanging data among them is afrequent requirement in many business scenarios. This typically involves one or many source systems, an intermediary processor, and one or many destination systems. Some organizations invest in purpose-built solution suites such as Data Warehouse, Master Data Management (MDM), or Extract, Transform, Load (ETL) platforms, which, in-theory, cover a wider spectrum of requirements.

Welcome back to Yellowfin Japan’s ‘How to?’ blog series! In our previous blog, we went through how to capture data using Yellowfin's Data Transformation flow, and the preparation and steps for creating reports using Yellowfin View. It may seem like a lot of simple work, but as the number of reports to be created increases, the importance of data preparation becomes far more apparent. So, what about after you’ve done all the setup? Well, it’s now time to create reports!