Data Analytics

Taking otherwise nebulous data and transform it into something useful

In between data and effective decision making is the data analyst. At Reliant Technologies, our team members take otherwise nebulous data and transform it into something practical and usable for prediction and prescription. Our creativity and forward thinking in this regard places us on the leading edge of development in the industry and allows us to harness cutting edge methods.

The application of data analytics allows for easy data dissemination to attain a common operational picture for an organization. This capability provides a boon to operational efficiency that saves time and energy, allowing it to be redirected elsewhere. A well-developed common operating picture improves collaboration and can provide the team with much-needed situational awareness.

With our data analytics we can remove ambiguities from complex situations to allow an organization to make key decisions. The output of our data analytics process provides actionable insights to our customers, allowing them to make the optimal decision quickly. The key capability to the product we provide is the ability to take raw data and develop meaningful actions with support from our data analytics.

Data analytics removes ambiguities in complex situations

Outputs of the data analytics process provides actionable insights to our customers, allowing them to make the optimal decision quickly. The ability to take raw data and develop meaningful actions is the key capability for our clients.

Natural Language

Natural Language Processing (NLP) is a widely applicable branch of software engineering that aims to understand semantic content in free text or speech data. Machine learning algorithms provide the capability for numerous NLP applications such as the speech recognition components of modern cell phones. Our data science team utilizes NLP capabilities in our software to provide our customers the ability to organize unstructured text data.

Computer Vision

Computer vision is a widely sought after capability in the software engineering industry. Machine learning techniques such as Convolutional Neural Networks have revolutionized the way we solve computer vision problems such as facial recognition for security systems and scene segmentation for self-driving cars. Our data science team utilizes computer vision techniques to perform image and video analysis.

Time-Series Modeling

Most of the data that engineers deal with on a daily basis has a temporal component to it. Machine learning provides a framework that allows time-series data to be modeled for a variety of tasks such as recognizing heart murmurs in EKG data and predicting component failure based on vibration data coming off of an aircraft. Our data science team applies time-series modeling techniques to tasks such as spares demand forecasting and maintenance prognostics.

Pattern Recognition

Machine learning provides multiple algorithms for detecting patterns in both supervised and unsupervised environments. Supervised algorithms provide the ability to detect patterns that are known by experts to exist in a given data source by allowing the experts to “teach” the machine how to recognize those patterns in the data. Our data science team applies machine learning techniques in multiple arenas to recognize patterns in our customers’ data.

Cyber Security Detection

Cybersecurity attacks are often associated with a significant change in some measurable metric over a short period of time. Machine learning provides and effective framework for modeling and understanding what metrics are considered normal or the ground truth of a particular system. Our data science team utilizes anomaly detection techniques to provide customers with early warning of changes to their environment.

Autonomous Control

Autonomous control systems have garnered a large amount of interest in places where people are attempting to build systems that successfully interact with the environment without human intervention. Machine learning, specifically Reinforcement Learning, provides the capability for these systems to learn what actions. Our data science team is researching the use of reinforcement learning to automatically generate difficult simulation scenarios designed to test the robustness of our customers’ platforms.