— Cignaling
DATA & INTELLIGENCE ARTIFICIELLE
The current explosion of data analytics is an opportunity for companies to innovate, to control their production and supply chain by optimizing processes and industrial performance, to analyze and develop their sales, profits and markets, to address new customers by improving their experience and profiling, and to create new offers by diversifying their business.
In terms of decision making, data science facilitates rapid and relevant decision-making based on data that is appropriately valued. A Business Intelligence or Big Data initiative thus enhances the value of data assets by making them a differentiating business factor.
Fraud detection, cyber-defense, purchase predictions, drones, autonomous vehicles, video games, personal assistants, human resources, predictive maintenance, artificial intelligence is already part of our daily lives, is developing at an exponential rate, and is revolutionizing the industrial sector in terms of system architecture and value creation.
Data science is now making the most of the explosion of data resulting from the multiplication of sensors, the decentralization of the infrastructure linked to edge computing, and the generalization of its use, as is the case, for example, in digital image processing applied to a wide variety of fields: medicine, geographic and weather maps, radar images, surveillance and biometrics, industrial control, forgery detection, microscopy, etc.
Data Engineering
Data storage in relevant data lakes, system interoperability, completeness and usability assurance: cignaling ensures upstream data quality, availability and usability as well as compliance with processing and storage regulations to provide data analysts with accurate and relevant data.
Data analysis
Classical analysis, Business Intelligence, Business Intelligence, descriptive or predictive statistical models, Big Data, mass processing, golden records, confidence rates, field profiling, Proof of Value, data visualization: cignaling guarantees the quality of the data, for fast, autonomous and value-creating decisions and the discovery of weak signals.
Big Data Analysis
Advanced Analytics, unstructured databases, data mining, mining, pattern detection and analysis, Hadoop, Hive, Hbase or Kafka clusters: cignaling performs predictive analytics and big data exploitation using advanced algorithmic models adapted to the content from heterogeneous data enriched with external sources.
Artificial Intelligence
Voice recognition, virtual assistants, behavioral or sentimental analysis, digital image processing, biometrics, supervised or unsupervised machine learning, neural networks, deep learning, edge computing: cignaling designs, implements and operates innovative solutions in decision support or autonomous machines.