ABSTRACT: The advent of disruptive technologies like Hadoop, Spark, Docker, Cloud Computing and Block Chain is ushering in the sea change of the procurement, deployment, development, and usage of enterprise software. Enterprise software has never been so de-centralized. New software is now introduced and tested in the bottom-up fashion instead of the traditional top-down way; IT infrastructure is now heterogeneous and built up incrementally instead of one-time expensive and lengthy deployment; rigid waterfall model is giving way to Agile and DevOps models; and technologies are no longer only limited to selected few IT personnel, more and more citizen analysts are leveraging the self-service tools to discover hidden insights in the data. The recent growth in machine learning, natural language processing, and open source tools, coupled with the growth of expertise in these areas, has opened the door to a wealth of problems involving automating previously manual processes, such as call center compliance, contract review, data extraction, knowledge management. This is projected to be a giant $1T+ industry, however, the primary challenge is the integration of specialized domain knowledge with layers of technology, and ability to integrate deep SME knowledge is the key to driving business success. KPMG is investing heavily in Data & Analytics and in distributed computing and artificial intelligence, and the Data & Analytics Center of Excellence to help Fortune 500 clients manage their challenges effectively. KPMG continues to embrace new technologies and ideas and foster the innovative environments with three revolutionary workspaces: Innovation Labs, Ignition Centers, and Insights Center. BIO: Gongqin Shen is a Data & Analytics Manager at KPMG, who is specialized in designing and building Data Warehouse, Data Lake, and ETL pipeline for enterprise customers. Since joining KPMG in 2014, he has worked with teams of software engineers, data scientists and data analysts to solve practical problems for clients in various industries. He received his PhD degree in Computer Science from Case Western Reserve University in 2005 and his bachelor degree in Computer Science from University of Science and Technology of China in 2001. BIO: John Lee is a Director of Data Science at the KPMG’s Data & Analytics Center of Excellence, the Lighthouse. He has expertise in unstructured data analytics, and methods from text mining, machine learning, natural language processing (NLP), and text analytics. Applications range from measuring political risk in news, automotive quality from social media, automating legal review of financial documents, and assisting in the M&A process through automation. He received his PhD in Electrical Engineering from UCLA.

Hosted by Professor Milos Ercegovac

REFRESHMENTS at 3:45 pm, SPEAKER at 4:15 pm