Apr 20, 2021

Data science serving business

  • Article
  • data science
  • artificial intelligence
  • Industry 4.0
  • big data
  • ai
  • robotics

In an increasingly connected world, managing massive amounts of data, or big data, is a major driving force of the economy. Today, it is easier to access thanks to several technologies that have made it possible to extract, organize and centralize the data to make it quickly accessible throughout the organization. For most businesses, the real challenge today is to clearly outline the actions that need to be taken based on the collected data and making the right decisions as a result.

  1. Data scientists

    You can count on data scientists to help you make informed data-based decisions and to find your way through the sea of bytes. Their role is to extract and exploit relevant information from big data, then organize, process and interpret it using statistical, mathematical and computer tools. These experts use powerful algorithms to make the data “speak.”

    Why data science?

    In the past, most available data was structured and small; it could be analyzed using simple tools. This is no longer the case today where most data is rather unstructured or semi-structured. Managing these types of data and analyzing them requires advanced skills such as using complex advanced analysis tools and artificial intelligence algorithms. These skills can be provided by a data scientist: data mining techniques, machine learning, deep learning and automatic natural language processing, to name a few.

    How data scientists play a role in Industry 4.0

    Industry 4.0 is all about industrial data analysis. Cyber-physical systems, the Internet of Things (IoT), robotics, digital twins, additive manufacturing, augmented reality, expert systems, autonomous devices and the development of innovative services are all highly related to data scientist expertise.

    There are many successful examples of data science improving revenues and efficiency while avoiding loss, hazards or serious system failures. For instance, predictive manufacturing assists manufacturers in maintaining a competitive edge in operational management control, in improving their production efficiency and in yielding rates with little overhead costs.

    Moreover, preventive maintenance tries to forecast the moment when a piece of equipment will fail to perform its task. Forecasting is not limited to failures or manufacturing procedures; it is also useful in other areas, such as demand management, supply chains, marketing and risk management.

    Artificial intelligence and robotics

    Robotization has been revolutionized by artificial intelligence. Today, data scientists want to optimize robots to become flexible, data-driven machines, instead of executing fixed, inefficient tasks. Computer vision applications are used in manufacturing, mostly at the quality control stage. They are faster and more accurate than classic quality control labour. Moreover, they are lower in costs for long-term production and can operate continuously 24/7 without any change in their productivity.

    Big data has opened new horizons for product development. Manufacturers are now able to better understand customer needs and discover hot trends. Data scientists provide companies with practical insight into figuring out which is more profitable: developing new products or improving existing ones. They can also help significantly in production process control.

    Thanks to big data analysis infrastructures and huge amounts of data collected from various monitoring sensors, data scientists are now helping companies increase their product efficiency. Various industries have experienced exemplary final product yield and quality improvement.

    Our data scientists at your service

    BBA data scientists are key players in optimization. With the latest condition monitoring technology, sensors combined with software and data analytics can track, measure and report on how your assets are performing in every aspect.

    In the next generation of automation, instead of ruling and controlling the whole system with rigid, predefined rules, control systems become more flexible in terms of the feedback received from the analyzed data. Thresholds, set points and other parameters are not a fixed value anymore. They vary based on intuitions from the analyzed data. This is a smart decision-making system that changes control parameters according to the analysis results. By finding meaningful patterns that guide them in improving operations, data scientists can drastically improve efficiency and productivity in all industries.

    Contact us to find out how data management can help improve your company’s productivity and profitability.

This content is for general information purposes only. All rights reserved ©BBA

Latest publications
See all
think it further
Contact us