Modern ABI Platforms for Healthcare Data Processing

Shaari, Hala; Durmić, Nermina; Ahmed, Nuredin

doi:10.1007/978-3-030-90055-7_14

Cited by 1 publication

(1 citation statement)

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“…One study [ 1 ] claimed that augmented BI helps in using available data for disease diagnosis, recommending potential treatments faster and more effectively, and improving drug development and manufacturing. Another study [ 25 ] found that augmented BI platforms help to improve the quality of services in the healthcare sector as they save time by helping doctors and specialists to track information easily. Leading augmented platforms have been technically analyzed in terms of applicability, general characteristics, and standard requirements for healthcare tasks.…”

Section: Related Workmentioning

confidence: 99%

Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence

Alghamdi

Al-Baity

2022

Sensors

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Lately, Augmented Analytics (AA) has increasingly been introduced as a tool for transforming data into valuable insights for decision-making, and it has gained attention as one of the most advanced methods to facilitate modern analytics for different types of users. AA can be defined as a combination of Business Intelligence (BI) and the advanced features of Artificial Intelligence (AI). With the massive growth in data diversity, the traditional approach to BI has become less useful and requires additional work to obtain timely results. However, the power of AA that uses AI can be leveraged in BI platforms with the use of Machine Learning (ML) and natural language comprehension to automate the cycle of business analytics. Despite the various benefits for businesses and end users in converting from BI to AA, research on this trend has been limited. This study presents a comparison of the capabilities of the traditional BI and its augmented version in the business analytics cycle. Our findings show that AA enhances analysis, reduces time, and supports data preparation, visualization, modelling, and generation of insights. However, AI-driven analytics cannot fully replace human decision-making, as most business problems cannot be solved purely by machines. Human interaction and perspectives are essential, and decision-makers still play an important role in sharing and operationalizing findings.

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Section: Related Workmentioning

confidence: 99%