Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK

Industrial big data and sensor time series data: Different but not difficult

Gopal GopalKrishnan (OSIsoft, LLC.), Hoa Tram (OSIsoft)
14:55–15:35 Thursday, 2/06/2016
IoT & real-time
Location: Capital Suite 12 Level: Intermediate
Average rating: **...
(2.25, 8 ratings)

Prerequisite knowledge

Attendees should be familiar with one or more of the following industries: oil and gas/petroleum refining, chemical and petrochemicals, energy and water/gas/electric utilities, metals and mining, or pharmaceuticals.


For 30+ years, industrial manufacturing, as well as energy and utilities, has dealt with large volumes of high-velocity data from automation controls and hundreds of thousands to millions of sensors—with each sensor collecting values every few seconds, some every millisecond or even several microseconds. These industries handle a variety of data from the various manufacturing operations management (MOM) systems in production, quality, maintenance, and inventory.

Gopal GopalKrishnan and Hoa Tram offer lessons learned from applying big data ecosystem tools to oil and gas, energy, utilities, metals, and mining use cases, outlining some specifics from a packaging line use case—a fill operation with hundreds of different SKUs—to show typical examples from predictive equipment maintenance, energy reduction, equipment/asset utilization, inventory, and product quality.

With physics and first principles material/energy flows to guide the analysis, visual and statistical analytics and machine-learning tools can be effectively leveraged for rapid wins. Gopal and Hoa explore some of the key drivers for quantifying business value, including manufacturing process and cost optimization, energy reduction, equipment reliability and predictive maintenance, consistency in product quality, inventory minimization, and demonstrate how tedious data preparation steps such as cleansing and shaping in OT-IT integration projects can now be done in just minutes and hours instead weeks or months; this is critical to iterative data exploration and allows you to work with the best in class for analytics and machine learning to find actionable information and then operationalize your findings into production.

Photo of Gopal GopalKrishnan

Gopal GopalKrishnan

OSIsoft, LLC.

Gopal GopalKrishnan is a solution architect in the Partners & Strategic Alliances group at OSIsoft. Gopal has been working with OSIsoft’s PI System since the mid-1990s in software development, technical and sales support, and field services. Previously, he was a product manager with a focus on enterprise and asset integration and PI data access. Gopal is a registered professional engineer in Pennsylvania. He is a member of the MESA technical Committee, the Education Committee, and the MESA Continuous Process Industry Special Interest Group. He actively participates in topics such as big data, data mining, energy efficiency, manufacturing intelligence, and sustainability (including green initiatives in facilities and data centers). Gopal holds a master’s degree in engineering and continuing education in business administration.

Photo of Hoa Tram

Hoa Tram


Hoa Tram is currently a partner solutions architect for OSIsoft. Hoa has worked in the software industry for nearly 20 years and has been with OSIsoft for the last 10. Attached to the company headquarters in San Leandro, CA, Hoa has been the development lead for the embedded Linux version of the PI Historian, the high-speed core communications layer of the PI system, and the OEM initiatives of OSI’s strategic partners. Hoa is an expert in the areas of data acquisition from the edge and analysis of that data in private and public cloud environments, working directly with OSI’s major equipment manufacturing and analytics partners to provide solutions to OSI’s customers in the industrial space ranging from increasing overall equipment effectiveness to cybersecurity.

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Picture of Gopal GopalKrishnan
Gopal GopalKrishnan
27/02/2016 14:48 GMT