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Quality decision making requires meaningful, reliable information. But does “”big data”” always meet those requirements?

Algorithms and software programs are designed to mine data into information gold, but questions about their effectiveness, the source and quality of the data, and additional and frequently hidden costs, can make the payback on big data prohibitive.

The central question remains – does big data really help you improve decision making?

Join JD Solomon to evaluate data collection, analytical tools, statistical approaches, and converting information into quality decisions. You’ll learn how to improve diagnostics and forecasting using big data and also examine several case studies ranging from ecosystems in the natural environment to transportation and utility systems in the built environment.


  1. Understand the range of data collection applications in different sectors, such as:
    1. Energy use in the power sector
    2. Traffic data and patterns from intelligent transportation systems
    3. Water use data from smart water metering systems
    4. Raw water quality from stream/river remote monitoring stations
    5. Equipment performance and asset health data from plant control systems
  2. Examine Statistical and analytical best practices for turning data into useable information
  3. Determine the role and limitations of data in the quality decision-making process
  4. Identify Key differences in problem diagnostics vs. prognostics and forecasting

This on-demand online class lasts 60 minutes and is worth 1.0 PDH (Professional Development Hour).

Course Type

Online Class

Delivery Type

On Demand, Online, Self-Paced

PDH Credit


Price (Member)


Price (Non-Member)


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