Big Data Storage Challenges for Industrial Internet

Industrial and Machine data is pushing the storage paradigms to new limits. With the Internet of Things connecting 26 billion new "things" by 2020, data centers will go through complete transformation to handle the Big Data. In order to make a large scale economic impact on country level infrastructure, the sensor data from the industrial machines such as jet engines, locomotives, power generation equipment and utilities have to be analyzed with very little latency. Such sensor data has to be married with other Enterprise data typically stored in Asset Management and other ERP and CRM systems. This session will showcase such challenges in context of Industrial Internet of Things. The framework for data ingestion, transformation, analysis as well as persistence of data, in context of streams and near-real-time batches will be discussed. We will address the different dimensions of Big Data namely volume, velocity and variety from storage and retrieval perspective.

Learning Objectives

Nature of Data from Internet of Things
Storage Challenges posed by Machine and Industrial Data
Nature of Industrial Internet of Things
Storage Paradigm for Data Analysis
Marrying Machine Data with Human Data