Descripción
Do you want to understand how your portfolio of projects are performing hosted on BIM 360 and Autodesk Construction Cloud? Would you like to maximum the value of your Autodesk analytics investment? This case study will cover a data product design developed by Walt Disney Parks and Resorts and Autodesk Consulting. We will give an overview of Disney's business requirements, KPIs, and metrics. We will list technical aspects of the data ELT (extracting, loading, and transforming) from Autodesk Data Connector. An area of focus will be the data engineering processes required to produce meaningful consolidated tables, where data from the Data Connector is sliced and diced to target customers' KPIs. The final products include an account users' management tool and three health-scoring systems, which are used to compare projects' health scores based on customized metrics. The products transform raw data into actionable insights that inform tactical business decisions. The scores generated equip Disney with detailed intelligence about the state of business.
Aprendizajes clave
- Gain an overview of business initiatives and pain points, KPIs for projects and users, and metrics developed and their measurements.
- Explore evaluations of the Autodesk Data Connector for customization, and look at an account user's management tool built based on Data Connector.
- Learn about metrics and the designing process for health-check scoring systems, including projects, users, services, and issues.
- Learn about value added to customers, and get recommendations on products' strategies for diagnostic and predictive analytics.
Orador
Liang GongHe is a structural engineer by training (PE) with a background in preconstruction/estimating, construction management, BIM/VDC and data science. He helps customers leverage the data they produce through the design and build process to generate actionable insights including forecasting and scalability. He also automates customized workflows with ACC Connect and Autodesk Platform Services. After graduating from Duke University, Liang is currently working on his second master's degree in Applied Data Science at University of Chicago, focusing on AI/ML as a part-time student.
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