Challenges in Big Data Computation: Insights from ASU Panel Discussion
Exploring fundamental challenges in computation within the big data era, this content delves into the complexities of handling social media data, emphasizing the importance of scalability, data relevancy, quality assurance, and data integration. Presented during a panel discussion at Arizona State University in 2014, the discourse navigates through the nuances of managing vast amounts of data to extract meaningful insights.
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Presentation Transcript
Fundamental Challenges to Computation in Big Data Era Huan Liu Arizona State University December 12, 2014 HKUST Panel Discussion 1 Data Mining and Machine Learning Lab
Fundamental Challenges in Social Media Data The more, the merrier only if we can tame it Scalability Not everyone cares about big data, but ALL need BIG information - Relevancy Garbage in, garbage out , how can we know the quality of the data we have? Veracity Make thin data thicker Integration Arizona State University December 12, 2014 HKUST Panel Discussion 4 Data Mining and Machine Learning Lab
