IEG 201402 Flutura M2M Data Science

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Information about IEG 201402 Flutura M2M Data Science
Business & Mgmt

Published on February 14, 2014

Author: informationexcellence



Information Excellence Group 2014 Spring "Business Analytics Industry Summit", M2M Data Science, Ganesh Parthasarathy, Sr Director, FLUTURA

FLUTURA: Unlocking the Ganesh Parthasarathy M2M Data Science

Unlocking The Next Industrial Revolution – M2M Data Science Flutura Decision Sciences and Analytics



What I actually do What my mom thinks I do KEEP CALM AND DIG DEEP INTO DATA What my friends thinks I do


Smart Infrastructure No span of steel will tolerate…neglect. But if service by generations who use it and spared manmade hazards, such as war, it should have life without end - Joseph Strauss, Chief Architect, 7 Golden Gate Bridge

Behind the Scenes Service Tension Temp Strain Incline Raw Data Hypothesis testing EDA Integrity Preventive Load Maintenance Monitoring Balancing • Damage Patterns Alarm • •Equilibrium •DetectionTrends •Load point Strain • cluster Classification • Maintenance • Prediction • Real time Alerts Data Models

Smart Infrastructure Load Balancing • Equilibrium • Load point cluster • Prediction Models Preventive Maintenance • Damage Detection • Classification • Real time Alerts Integrity Monitoring • Alarm Patterns • Strain Trends • Maintenance Data

Smart Assets powered by Cerebra “Enabling strong responses to weak signals at the last mile” is the key to sustainable “Zero unsafe behaviours and conditions” and to ensure our People are safe, our Environment is protected, our Assets are secure, and indeed our Reputations are intact - Srikanth M, Co-Founder of Flutura 10

Behind the Scenes Crrnt Voltage Temp Events Service Raw Data Hypothesis testing EDA Device Safety • How healthy is the device? • Which device needs attention? • Is there any device that are critical? • Which parameters are making the device unhealthy?

Smart Grids powered by Cerebra "An analysis by the Electric Power Research Institute estimates that the implementation of smart grid technologies could reduce electricity use by more than 4 percent by 2030. That would mean a savings of $20.4 billion for businesses and consumers around the country..." - President Obama White House Press Release- October 12 2009

Behind the Scenes SCADA Smart Meter Tamper Events Outage Events DTR Raw Data Hypothesis testing EDA Peak Load Frequent Stress Outages • • • • • You can save 3% on your $188 Billion estimated energy bill for every degree value of economics losses you lower your thermostat per year in USA U.S. power plants emit roughly July 2012 India 2.4 billion tons of CO2 per blackout was the largest year, approximately 40% of power outage in Indian the nation’s total global history warming pollution 620 million people, about 9% of the world population

Smart Grids Peak Load Stress • • You can save 3% on your energy bill for every degree you lower your thermostat U.S. power plants emit roughly 2.4 billion tons of CO2 per year, approximately 40% of the nation’s total global warming pollution Frequent Outages • • • $188 Billion estimated value of economics losses per year in USA July 2012 India blackout was the largest power outage in Indian history 620 million people, about 9% of the world population


Mantra-1 : Think “MVP-Minimum Viable Product”

Mantra-2 : Think “Biz backward … NOT Tech forward” 1. What is the business problem you are solving ? Tightly framed ? 2. Why is important to solve this problem ? 3. Is the business pain acknowledged ? 4. How would the end user “feel”? 5. Are budgets allocated ? 6. What is the actual use case to solve the pain ? Connect with business @ a deeper level !

Mantra-3 : Think “Data Signatures” • Text Mining • Collaborative Filtering • Scoring Model • Clustering • Decision Trees ML Algorithm can SPOT many Signatures

Mantra-4 : See Value in the Data

Mantra-5 : Think “Triangulation” The “Real Juices”

Mantra-6 : Think “Data Products” Focus on Actions Not Just Insights

Mantra-7 : “It’s not only science” End User is always a human being

FLUTURA’S M2M MANTRAS ANY QUESTIONS? Minimum Viable Product Biz backward … NOT Tech forward Data Signatures See Value in the Data Triangulation It’s not only science Email: Data Products

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