We are living in an era of data deluge and as a result, the term ‘‘big data’’ is appearing in many fields, from meteorology, complex physics simulations, manufacturing, systems engineering, assets maintenance, finance and business to healthcare.
Data science is the art of extracting meaningful insights and knowledge from data. It is a discipline that relies on mathematical tools, artificial intelligence, computer science, and data visualization to uncover key patterns within the data.
In the industrial field, the data enables production optimization, prediction and optimization of downtime, quality improvement and costs reduction. However, the amount of data delivered within industrial organizations can be overwhelming and it is generally unstructured and heterogeneous, especially since the advent of the Internet of Things (IoT). Organized and analyzed correctly, this information has the power to create more intelligent and business savvy organizations.
Data Science gives power to data to give competitive advantage and change decision-making processes by using efficiently data. In the next few years, business disruption will be triggered by data science and will offer efficient solutions for industrial specific needs to reduce unplanned downtime, minimize maintenance costs, find causes for equipment malfunctions and understand data patterns.
Assystem’s Data Science is based on multidisciplinary disciplines approach using physical modeling, statistics, artificial intelligence, and empirical knowledge.
With its consulting experience and engineering expertise in different industrial sectors, Assystem has a unique versatility to understand the specific mechanisms of each industry. We afford solutions for data analytics and artificial intelligence to turn our customer’s data into knowledge and business decision. We help them transform documents based approach into a data based approach beefed-up with advanced analytics as well as transforming empirical knowledge into mathematical and AI models with high accuracy.
Assystem approach is based on two fundamentals basics: the good qualification of our clients’ needs and the production of the right level of data to create the expected benefit.
We developed a four level approach to offer our clients the adequate service in accordance to their specific needs and maturity:
Data science advisory: To identify and define the outcome expected from your data. We co-design with you and our experts the best data-driven solution for your business.
Data science exploration: To help you understand and extract the insights from your already available data. You will be able to achieve a root cause analysis or pattern extraction in fast exploration.
Data science solution: To provide you the data-driven solution from the data capture to the data visualization and advisory data generation developed.
Data science training: To introduce data science capabilities and business outcomes through an adapted and practical program for your executives and engineers.
Data ingestion and Big Data storage
Our partnership with Saagie offers us the best data fabric system. Our data scientists have access to the most advanced tools for data ingestion, big data storage, and real-time processing, including: GE Predix, Siemens Mindsphere, IBM Watson, PTC Thingworx
Agile delivery and lean process
We work with partners specialized in the design thinking methodology as well as scrum methods. We also use an agile approach in our data science advisory and our training workshops.
Data engineering and artificial intelligence
We use advanced data engineering techniques such as Apache, Hadoop, Elasticsearch. As well as cutting-edge artificial intelligence frameworks such as Pytorch, Keras and TensorFlow
We are dedicated to the engineering of infrastructures and energy sectors which gives us strong expertises in different fields: mechanical, electrical, instrumentation & control systems, information systems, civil engineering, etc.
We help you implement a Prognostics and Health Management (PHM) approach to set up the best process for condition based maintenance and predictive maintenance.
We use Natural Language Processing and machine learning techniques to extract the relevant information from your documents faster and efficiently allowing you to move from document based engineering approach to a data-driven engineering approach.
We use multivariate statistics and unsupervised machine learning to help you finding root causes for equipment malfunctions and understand data patterns with data-driven root cause analysis. We also use operation search and optimization techniques to improve decision-making through advanced analytics.
Techniques applied to images and videos such us object detection, image processing for measurement, OCR (Optical Character Recognition) and image classification.
After exploratory analysis, we identify issues and implement data monitoring solutions. Animations and charts let speak the data with a better manner then unwieldy spreadsheets.