{"id":10492,"date":"2017-11-15T07:00:06","date_gmt":"2017-11-15T15:00:06","guid":{"rendered":"http:\/\/www.palada.net\/index.php\/2017\/11\/15\/news-4264\/"},"modified":"2017-11-15T07:00:06","modified_gmt":"2017-11-15T15:00:06","slug":"news-4264","status":"publish","type":"post","link":"http:\/\/www.palada.net\/index.php\/2017\/11\/15\/news-4264\/","title":{"rendered":"Smart Connected Operations \u2013 Where is the data going?"},"content":{"rendered":"

Credit to Author: Guest Blogger| Date: Wed, 15 Nov 2017 13:07:24 +0000<\/strong><\/p>\n

\"Andrew <\/p>\n

Andrew Hughes joined the LNS Research team in May of 2015 and is a Principal Analyst with his primary focus being research and analysis in the Manufacturing Operations Management (MOM) practice. Andrew has 30 years of experience in manufacturing IT, software research, sales and management across a broad spectrum of manufacturing industries.<\/em><\/p>\n

In our last blog on Smart Connected Operations<\/a>, we looked at the trend of connecting new data sources, Smart Connected Devices (SCD), directly to the Industrial Internet of Things (IIoT). It is clear that SCDs are proliferating and will bring new information to manufacturing enterprises. That data is already finding uses in some of the low hanging fruit of the IIoT such as predictive maintenance. However, the promise of the IIoT goes far beyond a few data points gathered by new smart devices.<\/p>\n

Thinking Big Data<\/strong><\/h4>\n

Big Data Analytics is one of the key promises of IIOT and Smart Manufacturing; while we do not want to\"\"<\/a> \u00a0go into depth about the different levels of sophistication in analytics, it is worth considering briefly how we could define big data analytics. I like to use a simple test. Does your system answer questions you did not even know to ask? If yes, you are well on the way to truly smart analytics.
To achieve prescriptive analytics with big data (The top right quadrant), you are going to need to gather data from many sources. Being manufacturing operations people, we tend to think mostly about the manufacturing data. But to get maximum benefit from our IIoT platform, we will want to bring together data from many sources.
As industrial companies continue to drive digital transformation, they want new applications for the ever-increasing volume of data being collected and stored in the IIoT platform. Many applications will take disparate data and use it in new analytical apps, and in ways that were not considered when the data was originally being configured. We need to be able to handle data in new ways, but also to prepare in advance.<\/p>\n