August 11, 2021


Industry 4.0 Continued

The blog post last week began to explore careers relating to Industry 4.0: where actuators and smart sensors capture and analyze data in real-time, providing plant employees the ability to drive accurate and fast business decisions. However, this week’s focus will shift to a career in big data, another element of Industry 4.0. Big data in manufacturing means the collection of large sets of statistics at every stage of the manufacturing operation, including devices, operators, and machines.

Big Data Concepts

Big data for manufacturing is often collected and stored in data lakes on the cloud. Processing this data occurs in graphics processing units (GPUs) that allow graphics programmers to create more realistic images with growing popularity in artificial intelligence and creative production. A significant assembly of hardware, software, and infrastructure is necessary to support the collection and analysis of big data. A key in analyzing the data is to find the true root cause of an issue to drive continuous improvement. It is also essential to separate correlation from causality with certainty. Linear regression is a standard technique for finding correlation and covariance in large and noisy data sets.

Image Credit: Christina Morillo from Pexels

Big Data Advantages in Manufacturing

Effective and efficient collection and analysis of big data provide several benefits to manufacturing operations including:

  • Faster integration of automation – An example is where robotics implementation complements humans to increase operational efficiency.
  • The ability to predict machine failure & reduce downtime – Analyzing the collected data can indicate when breakdowns or halt issues would occur, allowing self-correction and self-maintenance to improve uptime.
  • Enhanced product quality & lower costs – Automated quality tests are more reliable and allow ongoing monitoring to adjust the process in real-time to reduce or eliminate manufacturing defects, which improves quality while reducing testing costs and errors.
  • Improved research – The opportunity to automate data collection allows for larger data sets that avoid human error and collect significant amounts of statistical information.
  • Greater customer service – The use of advanced sensors allows for buyer customization of products. The applicable data tracking notifies operators or processes to monitor conditions and specifications that lead to made-to-order products that improve overall customer satisfaction. Where possible, collecting data from customers will also allow the further enhancing of products to meet their needs more fully.
  • Increased competitiveness -Sixty-seven percent of manufacturers that have adopted big data collection and analysis, and resultant improvements have upgraded their competitive position.
These are just a few of the opportunities available to production plants that are successful in utilizing big data.
Every company has big data in its future and every company will eventually be in the data business.
Thomas H. Davenport

Data Scientist Jobs Outside of the Tech Industry

A typical career path for data scientists is to pursue their dream job at a global tech firm. However, the advantages of looking at opportunities with other industries are:

  • Working with related technologies, such as genetics and the Internet of Things (IoT).
  • The opportunity to analyze data from various sources like machines, manufacturing processes, and wearables.
  • Expanded geographic living options beyond those in the tech space.
  • A chance to work in other industries with a greater personal appeal.
  • Existing experience in a non-tech industry.

The author shares information on five other sectors outside of the tech industry to include industrial goods. Similar salaries to the tech sector are possible with $5 billion+ revenue companies in the manufacturing industry. The job can be recession-proof if the particular product is considered essential. The types of expected projects can include productivity optimization, research and development, and worker safety. The optimal skillset would consist of knowledge of advanced engineering methods, experience in collecting and analyzing real-time data, and the ability to work well in a team setting.

Education Options

Those interested in a career in collecting and interpreting big data have a wide variety of education options. There are many big data and data analytics certifications that can improve the potential of an individual to work in this field. A Bachelor of Science in Information and Decision Science is an offering at the University of Illinois Chicago. The Virginia Commonwealth University Master of Decision Analytics program can be completed in as little as 16 months. A Ph.D. in Decision Science at Duke University is available for those interested in a terminal degree. Finally, a fast-track post-graduate program in Data Science and Business Analytics is available at the University of Texas at Austin in the Texas Executive Education department.

Big Data Careers

An individual interested in a career in big data should be proficient in 1) business acumen, 2) technical know-how, 3) communication skills, 4) stakeholder management skills, 5) critical thinking capability, 6) presentation skills, and 7) data visualization skills. The big data field anticipates growth of 12 percent by 2028, per the U.S. Bureau of Labor Statistics, with a projection of 546,200 new job openings. A career in this area can be lucrative, with entry-level salaries starting around $80,000 and working up to an annual salary range of $130,000-$222,000 for a big data engineer.

Key Takeaway

Big data can enable manufacturers’ reassurance that they are producing high-quality products most cost-effectively. The result of efficiently and effectively monitoring real-time data is to see the future through predictive analytics that allows corrective actions before an issue arises. But, of course, the best kind of production issue is the one that never occurs.

First Step

Simplilearn has a tutorial on How to Build a Career in Data Science that provides a good overview of a career in big data. There, those interested in learning more about working in this field can find a comprehensive video about the role of a data scientist.

My Gratitude

I continue to marvel at the growth in technology capability that is also continuing to decrease in cost. Big data is becoming a reality for all sizes of manufacturing operations. As someone old enough to have been excited to play Pong, one of the first computer games, I continue to be grateful to those that have developed technology that is creating a better world.

Sneak Peek

Next week, the blog topic will continue with the shift to expand the employment pool for the manufacturing sector.

To learn more about our work or to read more blog posts, visit

Cover Image Credit: by Nataliya Vaitkevich from Pexels

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