Visible to the public Bringing AI to BI: Enabling Visual Analytics of Unstructured Data in a Modern Business Intelligence Platform

TitleBringing AI to BI: Enabling Visual Analytics of Unstructured Data in a Modern Business Intelligence Platform
Publication TypeConference Paper
Year of Publication2018
AuthorsEdge, Darren, Larson, Jonathan, White, Christopher
Conference NameExtended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Date PublishedApril 2018
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5621-3
KeywordsAI, business intelligence, Data, HCI, pubcrawl, resilience, Resiliency, Scalability, visual analytics, work factor metrics
Abstract

The Business Intelligence (BI) paradigm is challenged by emerging use cases such as news and social media analytics in which the source data are unstructured, the analysis metrics are unspecified, and the appropriate visual representations are unsupported by mainstream tools. This case study documents the work undertaken in Microsoft Research to enable these use cases in the Microsoft Power BI product. Our approach comprises: (a) back-end pipelines that use AI to infer navigable data structures from streams of unstructured text, media and metadata; and (b) front-end representations of these structures grounded in the Visual Analytics literature. Through our creation of multiple end-to-end data applications, we learned that representing the varying quality of inferred data structures was crucial for making the use and limitations of AI transparent to users. We conclude with reflections on BI in the age of AI, big data, and democratized access to data analytics.

URLhttps://dl.acm.org/doi/10.1145/3170427.3174367
DOI10.1145/3170427.3174367
Citation Keyedge_bringing_2018