Data Science

The right data, in the right context and from the right perspective. Reduce uncertainty with the information advantage data gives you, and use it to improve business performance.

Big Data Big Value e-book by Interlogica

Want to know more about Big Data?

Many things we do every day generate an enormous amount of data: connected smartphones, clicks on the web, smart meters, IoT devices, voice requests to Google, Siri or Alexa. Huge volumes of data, varied in source and format, that can be analysed in real time: all of this is Big Data.
Yet the truly revolutionary force that is upsetting existing business models and ecosystems is not the data itself, but its analysis. Companies that use Big Data Analysis make faster, better-targeted decisions and become more competitive in the market.

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What we can do for you

What Big Data is

Yet the truly revolutionary force that is upsetting existing business models and ecosystems is not the data itself, but its analysis. Companies that use Big Data Analysis make faster, better-targeted decisions and become more competitive in the market.

What opportunities for your business?

There are many practical examples of using data to gain a competitive advantage, predict behaviour or understand the effects on a process or product, across the most diverse fields and applications. Here are a few:

New product development and offer optimisation

Well-grounded decisions based on real data

Customer profiling and management

Competitor analysis

Failure rate prediction

Neural networks

CRM

Recurring schemes and patterns

Tailor-made solutions

There is no universal solution to specific problems: each problem must be tackled from scratch, by studying the context and the goal to be reached.

What can be done with the data set you have? A great deal. Set a goal and we will analyse your needs together. Our approach is focused on results and on maximising Time to Market.

Domain knowledge

In this first phase we enter your world and acquire the knowledge we need to understand your organisation

Forming opinions

We analyse the information gathered to form informed opinions, providing a solid starting point

Analysis

We dig into the information gathered and examine the data collected, identifying trends and relationships.

Data interpretation and visualisation

We study the data collected, organise it and represent it visually.

Reporting

We deliver a full report of all the data collected and the answers to the questions asked.

Refinement

In this last phase we take action to improve the process based on the data in the report.

Data is indeed wealth, but translating it into value is not as simple as it may seem. Without an understanding of what data represents and an intuition of what can be obtained from it, it is nothing more than space taken up on a hard drive.

alberto bianchi | data scientist

The potential of strategic opportunities

Data streams are essential for in-depth interpretive or predictive analysis that supports decision-making and creates a competitive advantage in every industry. As the market evolves, consumers ask for ever smarter services that can also solve problems quickly.

The new challenges are about the speed and intelligence of Fast & Smart solutions: real-time analysis and the use of Deep Learning and Machine Learning to gain a real competitive advantage.

TUNE Confederation
Territory, Utilities, NEtwork

Big Data: innovation and competitiveness

New data-driven innovation models towards a common European data space. The European project TUNE – Territory, Utilities, NEtwork promotes the creation of a shared Data Marketplace to encourage the growth of the private sector, scientific progress and the reuse of information in the public sector.

The TUNE project

Pooling some data to understand how it can be used and shared without compromising privacy, confidentiality and sensitivity. The data confederation allows participants to be more competitive and to play a bigger role in data-driven innovation.
Every company, institution and citizen/consumer could potentially benefit from shared data to pursue their own vision.

Our contribution

Interlogica created an experimental environment, a shared pool of data (proprietary and open) from which to extract information.
The data was used to explore two questions and highlight any correlations between areas in the context of separate waste collection:

A possible correlation between green waste disposal and the weather (seasonality).
A possible correlation between good recycling habits and reliable bill payment.