Big Data analytics for test and measurement (T&M) is gaining attention as many industries have realized the benefits of implementing Big Data analytics for T&M. Real-time analytics for maintaining the structural health of safety-critical components, reducing product development time, and ensuring quality maintenance can all be achieved by implementing Big Data analytics for T&M. The study identifies popular application areas where Big Data analytics is being implemented for T&M, along with an opportunity analysis for 3 of the industries where the adoption of Big Data analytics has been high.
Research Aim and Objectives
Aim The aim of the study is to identify and understand Big Data analytics for test and measurement (T&M) worldwide. For the purpose of this study, other industries were considered, such as T&M in energy, aerospace, automotive, and other manufacturing industries such as semiconductor manufacturing and utilities manufacturing.
Objectives - Identify Big Data as a Mega Trend that will influence a wide range of testing activities, processes, and perceptions. - Define Big Data analytics for T&M and understand its impact from both a quantitative and qualitative perspective and offer futuristic predictions on trends. - Analyze and identify the relevant developments within Big Data analytics for T&M. - Identify the key industries that embrace Big Data analytics for T&M. - Carry out a macro-to-micro analysis to understand the unmet needs or inherent business opportunities of relevant industries.
The Future of Big Data Analytics for T&M—Key Findings - Big Data analytics for T&M is growing at a CAGR of % and is expected to reach $ Billion by 2021. - Big Data analytics for T&M is gaining popularity as industries strive to reduce the cost spent on testing and inspection. - Varying with the industry, product development costs can be reduced by almost %, operating costs can be reduced by almost %, and maintenance costs can be reduced by %, if Big Data analytics is applied for testing. - Research and development (R&D), risk management, and asset management are the key application areas where Big Data analytics for T&M is being utilized. - Tough competition can be expected in this space, but participants with industrial expertise would gain leverage if their target customers are Tier II and Tier III companies. Tier I companies show a preference for information and communications technologies (ICT) companies such as IBM and SAS.
Table Of Contents
Global Big Data Analytics Market for Test and Measurement 1. EXECUTIVE SUMMARY
Executive Summary Research Aim and Objectives The Future of Big Data Analytics for TandMâKey Findings Market Definitions Definition of a Mega Trend Why do Mega Trends Matter?
2. BIG DATAâDEFINITION
Big DataâDefinition What is Big Data? Four Dimensions of Big Data Types of Data-enabled Services Big Data Evolution
3. BIG DATA ANALYTICS FOR TandM
Big Data Analytics for TandM Big Data Evolution Sources of Big Data from the Engineering Domain Big Data Application Areas for TandM Pillars of Big Data Analytics for TandM Customized Data VisualizationâThe Need of the Hour Benefits of Implementing Big Data Analytics for TandM Implementation Challenges