SOLUTIONS

Data Marts

A Data Mart is a subset of a data warehouse which is more focused and oriented to a specific subject or business line. Users without expertise in working with databases and data warehouses can simply consult data marts to get access to domain-specific data for reporting, analysis and supporting the decision-making processes.

We are using several data marts to accelerate our business processes by avoiding the time-consuming tasks of collecting information directly from the source databases.

IoT

Internet of Things (IoT) refers to a system in which the physical objects, devices or machines are connected to the Internet by sensors. IoT-based technologies can produce vast quantities of data regarding their sampling frequencies and running time. These sensors can provide data from different sources.

Passive data which means that the data is readable and accessible through an API Active data which refers to a steady stream of data samples Dynamic data from smart sensors that can communicate in a bidirectional way with IoT applications.

Database Silos

A Data Silo is an isolated repository which has remained fairly segregated from other parts of the system's architecture. Since data silos are closed off from other elements in an organization, generally they have been considered as a problem for efficiency and data integration of the system.

However, at ERIS Innovation we are heavily investing in opening up data silos applying complex network design, modern cloud services and advanced software management tools.

Legacy Data

Legacy data is a kind of disparate data which nearly comes from everywhere, including existing relational/hierarchical or object/relational databases. However, the main sources of legacy data are those from antiquated and outdated legacy systems and applications which many companies still keep running them for some convincing reasons to avoid costly and sophisticated changes, damaging business stoppages or even privacy or political issues.

At ERIS Innovation we are planning to extract, transform, anonymize and eventually convert disparate data not only from legacy systems but also from other disparate data sources such as some ERP (Enterprise Resource Planning) systems or their related modules like CRM (Customer Relationship Management) systems for example.

Cloud Applications and Cloud Data Sources

As Cloud Computing continues to deliver IT services via the Internet, efficient data modeling is becoming more and more important for many companies and organizations to make the most benefit out of the cloud-based data sources.

At ERIS Innovation we are developing a broad framework that employs several service- level or application-level APIs to provide access and functionality for a cloud environment in addition to connecting the application-layer with the cloud and underlying IT infrastructure such as ERP and CRM cloud-based application extensions.

Predictive Modeling

The high proficiency in Predictive Modeling has helped us to develop some accurate and novel Forecasting methods which delivered quite acceptable and encouraging results in the field of Energy Price Forecasting. These ingenious techniques enjoy the benefits of the human being's neural system as well as the human reasoning capacities that increase our enhanced capabilities for making accurate and reliable predictions of economic indicators, product's sales, good's prices and customer demands.

Optimization

Optimization is the process of maximizing the performance and efficiency of a system, while minimizing the costs without violating the system's constraints. Optimization techniques provide a mathematical model of a business which quantifies the tradeoffs between numerous objectives and bring valuable help to decision makers. At ERIS Innovation we are highly experienced in solving several complex and multi-objective optimization problems applying different optimization algorithms ranging from statistical approaches like Non-Linear Mixed-Integer Programming (NLMIP) to metaheuristics such as Genetic Algorithms (GA), Simulated Annealing (SA) and Particle Swarm Optimization (PSO).

Anomaly Detection

Anomaly Detection is the identification of unexpected or abnormal behavior in the data, also referred to as deviations or outliers. Anomalous data points could be potential faults or failures in the system indicating the possible financial/banking fraud, health problems in a society, cyber-security attacks and etc. In data mining, anomalies do not necessarily represent failures and sometimes they are only indicative of some new trends or behaviors for example in the consumer buying habits.

Machine Learning

Machine Learning is a crucial part of Artificial Intelligence that makes computers and machines to be able to learn without being explicitly programmed. Machine Learning as a novel technology in the field of computer science refers to the process of designing and developing complex models and algorithms that themselves can learn from data and adjust the system actions accordingly. We are highly capable of developing and devising cutting-edge Machine Learning-based methods and algorithms with the both supervised and unsupervised approaches.

Deep Learning

Deep learning is a set of algorithms in machine learning that attempt to learn in multiple layers of non-linear transformations. Deep structured learning has surpassed most of conventional methods in many learning tasks such as voice or image recognition. Thanks to our profound and extensive mathematical knowledge and also our full access to high performance computational facilities, at ERIS Innovation we are developing several Deep Learning software programs to mimic the neocortex's activities by huge arrays of virtual neurons in an artificial neural network to provide effective and practical solutions from personalized product engineering to adaptive algorithmic trading and investment.

Pattern Recognition

Pattern Recognition is the science of analysis, extraction and identification of patterns in data. Automatic machine recognition is a key ability of computers to be intelligent enough for recognizing time trends within datasets or visual patterns in an image for example. At ERIS Innovation we aim to make the process of studying and detection of patterns explicit, such that the computer machines would be able to recognize specific behaviors or data classes automatically to support and develop smart decision making modules.

Graphics Frameworks

By using different graphic libraries, we have developed our own framework in order to facilitate visualization of massive quantities of data. ERIS Graphic Framework deeply integrates processed data to view, easily, enormous amounts of data to help decision makers with their job.

Presenting data visually allows us to uncover surprising patterns that wouldn't be apparent from simply looking at stats. In order to create data pipelines, to discover answers and to create new analysis for business users, you need to have sharp visualization. It will help you better understand what's happening with your business, your organization or your clients.

Mobility

With millions of mobile devices in use for business purposes and other millions owned for personal use, it is deeply known that mobility is and will continue to be the way we communicate with each other.

So, in order to provide our customers with the necessary tools to display all collected and analyzed data, mobility has become one of our main line of actions.

At ERIS Innovation, we are experts in developing applications with native IOS, Android and Windows Phone apps as well as other hybrid mobile systems, that allow us building cross-platform mobile apps with Standard Web-based technologies like HTML, JavaScript or CSS.