We are advisor for Data modelling and our solution span different areas: Business Intelligence, Advanced Analytics, Modern Analytics, Data Modelling, Machine Learning, Artificial Intelligence and IoT
The development of a project requires experience, flexibility and a method able to achieve results, rapidly, qualitative and efficacy. The aim is to find as soon as possible the critical areas on which intervene.
The most important thing is evaluating the ‘as-is’ situation, identify needs/requirements, then start with the development of the Infrastructural Design, which allow us to understand the best strategy to adopt and choose a common dictionary.
The Proof of Concept is a fundamental path, which has to be done before starting with the operative part of the project. It allows to make clear the scope of the project itself and to show quickly what should be the road to the result, providing a Long period vision, able to avoid next misunderstanding or delay on the release of the project.
Thanks to the ‘Agile’ methodology used, continuous releases are provided, able to make the model more efficient, the project faster and more effective in its implementation.
The Proof of Concept develops a data-driven preliminary model in a very short time, so that stakeholders can work immediately on a high-performance analytical model, giving a concrete idea of what the project result will be.
Modern Data Analytics means the set of all paths and ‘Cloud tools’ through which an organization can collect structured and unstructured data to analyse and make operational and strategic decisions, in an easier manner.
Optimize, monitor and integrate business processes, relying on data from machines, objects and devices in order to make performance more effective, is the task of IoT Smart Projects.
Data Modern Analytics and IoT Smart Projects allow you to govern data from both structured and unstructured databases as well as objects. By generating a Multi Stakeholder, platform-as-a-service, and Infrastructure as-a-service support infrastructure, we enable an agile and optimising environment toward the functional areas of:
The goal of Modern Data Analytics is to make business information accessible, consistent, reliable, secure and usable, thanks to modern tracking, monitoring, analysis and presentation tools Interactive.
The purpose of IoT Smart Projects is to control the processes based on the interaction among person and things. In addition, predict state and operation phenomena by integrating different business processes.
Data modelling is the process used for defining and analyse data requirements you need.
Data Modelling is the implementation of a model, thus, the ‘figurative’ representation of data structure, objects and database rules, required for the governance among data. Modelling translates information from the real-functional world to the informatic ones.
Data modelling aim is to make more effective the processes of different business functional area, trough customizable models, that together with the managerial experience, can make easier and faster the selection of the best strategy to adopt.
Data Virtualization associates’ company available data among them, without being transferred to a new, entirely dedicated physical data structure.
Its purpose is to produce a connection to data sources in the most useful format depending on the scope of use, in Compliance and focused Data Governance fields.
Data are available through simple and intuitive interfaces, and the access to data is accelerated through caching data structures.
Machine Learning is applied when a historical set of data exist. They will be then analysed through specific algorithms in order to develop time series.
It allows to predict phenomena I different fields: from the Fintech, manufacturing – maintenance, medical and Sustainability green economy.
Its purpose is to predict risks related to production and/or machines maintenance, know the expected benefits, production and budget.
Machine Learning aim is to develop models able to optimize, monitor, predict and integrate business processes. This allow company to make more efficient the business and take decision based on concrete data.
Data presentation is the set of all techniques used for representing graphically data and explore them interactively.
This is a fundamental step in Analytics field, it is expressed in a structured approach aimed at creating visual and interactive reports, which allow those who observe them, to interpret them easily and capture quickly the most relevant information.
The aim of Data presentation is to represent information in dynamical, flexible, captive and customized dashboards.
Dashboard are made in the best format for you, provided in a way that allow you to have the data access in every moment with any mobile device (Smartphone, tablet, pc…)
Data presentation shows analytical model, with eye-catching, simple and intuitive shapes, through flexible dashboards, which ‘zoom’ on data features and challenge them real-time.
The purpose of a well-done and good data presentation is to create a culture of data within the company, where everyone, who has permission, can access it quickly. This allows to avoid waste of time when analysing and interpreting data, incentivize collaboration between departments, enable each manager or team member to understand statistical reports and optimize decision-making from a data driven perspective.
Evaluation of client “as-is” and “nice to have”
Identification of the most effective path to act
Design a roadmap visible with a Proof of Concept – PoC
Build a team with the people involved into the project
Analysis results presentation
Knowledge and method transfer to the client